COMPARATIVE STUDY OF GROWTH AND PRODUCTIVITY OF …

COMPARATIVE STUDY OF GROWTH ANDPRODUCTIVITY OF MAIZE (Zea mays L.)UNDER DIFFERENT JHUM CYCLES OF

MIZORAM

THESISSubmitted in partial fulfillment of the requirements

for the degree ofDOCTOR OF PHILOSOPHY IN FORESTRY

By

LALRAMMUANPUIA HNAMTEMZU/PhD/279 of 09.06.2009

Department of Forestry,School of Earth Sciences & Natural Resources Management

Mizoram University,Aizawl -796004

2016

MIZORAM UNIVERSITYAIZAWL – 796004, MIZORAMDEPARTMENT OF FORESTRY

CERTIFICATE

This is to certify that the thesis entitled “ Comparative Study of Growth and

Productivity of Maize (Zea mays L.) Under Different Jhum Cycles in Mizoram”

submitted by Mr. Lalrammuanpuia Hnamte for the degree of Doctor of Philosophy in

Forestry embodies the record of original investigation carried out by him under my

guidance and supervision. He has been duly registered and the thesis presented is

worthy of being considered for the award of the Ph.D degree. This thesis or any part

thereof has not been submitted for any degree of any other University.

Date: Mizoram University (Prof. B. GOPICHAND)

Supervisor

_______________________

MIZORAM UNIVERSITYAIZAWL – 796004, MIZORAMDEPARTMENT OF FORESTRY

DECLARATION

I, Mr. Lalrammuanpuia Hnamte, hereby declare that the subject matter of this

thesis is the record of the work done by me, that the contents of this thesis did not

form basis for the award of any previous degree to me or to anybody else, and the

thesis has not been submitted by me for any research degree in any other University/

Institution.

This is being submitted to the Mizoram University for the degree of Doctor of

Philosophy in Forestry.

(LALRAMMUANPUIA HNAMTE)

Candidate

(Dr. S.K. Tripathi) (Prof. B. GOPICHAND)

Head Supervisor

CONTENTS

Page No.

Acknowledgement i

List of Tables ii - iv

List of figures v - viii

List of Photo Plates ix

List of Abbreviations used x

Chapter 1 Introduction 1 - 45

Chapter 2 Review of Literature 46 -79

Chapter 3 Study Area 80 - 87

Chapter 4 Materials and Methods 88 - 98

Chapter 5 Results 99 - 150

Chapter 6 Discussion 151 - 157

Chapter 7 Summary and Conclusions 158 - 160

References 161 - 192

ACKNOWLEDGEMENTS

I express my heartfelt gratitude to my supervisor Prof. B. Gopichand,Department of Forestry, Mizoram University, Aizawl for his benevolentguidance and advice throughout the course of the study. Without him, thisresearch work will not be completed.

I thank Dr. S.K.Tripathi, Head, Department of Forestry and otherfaculty members for their support during my research tenure.

My deepest thanks goes to Dr. C. Lalrammawia, for helping meanalyze my data and in shaping up my thesis. The never endingencouragement, endless support and immeasurable help from you and yourfamily is appreciated.

I am also thankful to the Principal and Staffs of Mizoram Institute ofComprehensive Education, Venghlui, Aizawl for giving me the time needed tocomplete my PhD.

I acknowledge Dr. David C. Vanlalfakawma for his valuable inputs inthe analysis of my research data.

I am indebted to my relatives for their untiring help, particularly inlocating experimental sites and in collecting data. Your encouragement andinvolvement from the get-go is vital for the completion of this work.

I owe much to my wife for her unwavering and diligent support. I alsoextend my deepest gratitude to my parents for their prayers, inspiration andconstant motivation. A simple thank you is insufficient.

I thank my friends and well wishers who have always helped at theappropriate time.

Most of all, I thank the Almighty God for bestowing countlessblessings and for granting me strength and opportunity to carry out thisresearch from the beginning till its completion.

Dated the ………., 2016. (LALRAMMUANPUIA HNAMTE )

i

LIST OF TABLES

Table 1.1 Composition per 100g of edible portion of maize (dry).

Table 1.2 Top ten maize producers in 2013 (FAOSTAT 2014).

Table 4.1 Table showing combination of spacing and fertilizer treatment plots.

Table 5.1 Monthly rainfall of 2010 showing the rainfall pattern during theexperimental period.

Table 5.2 Soil properties of 2JC, 3JC and 5JC before land preparation.

Table 5.3.1 Plant height at 15 days after sowing (DAS) under different spacing andfertilizer application levels in 2, 3 and 5 years jhum cycles. Mean± SEM.




Table 5.3.5 No. of leaves at 15 days after sowing (DAS) under different spacingand fertilizer application levels in 2, 3 and 5 years jhum cycles. Mean± SEM.




Table 5.3.9 Biomass at maturity harvest under different spacing and fertilizerapplication levels in 2, 3 and 5 years jhum cycles. Mean± SEM.

ii

Table 5.4.1 Length of cob under different spacing and fertilizer application levelsin 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.4.2 No. of Kernel rows per cob under different spacing and fertilizerapplication levels in 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.4.3 The effect of fertilizer application on number of Kernels per row underS1, S2 and S3 spacing in 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.4.4 The effect of fertilizer application on number Kernels per cob underS1, S2 and S3 spacing in 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.4.5 Test weight (wt. of 1000 grains) under different spacing and fertilizerapplication levels in 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.4.6 Grain yield under different spacing and fertilizer application levels in2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.4.7 Harvest Index under different spacing and fertilizer application levelsin 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.5.1 Effect of spacing on plant height at 15 days after sowing (DAS)under different levels of fertilizer applications in 2, 3 and 5 years jhumcycles. Mean± SEM.




Table 5.5.5 Effect of spacing on number of leaves per plant at 15 days after sowing(DAS) under different levels of fertilizer applications in 2, 3 and 5years jhum cycles. Mean± SEM.



iii


Table 5.5.9 Effect of spacing on biomass production at maturity harvest underdifferent levels of fertilizer applications in 2, 3 and 5 years jhumcycles. Mean± SEM.

Table 5.6.1 Effect of spacing on length of cob under different levels of fertilizerapplications in 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.6.2 Effect of spacing on kernel rows per cob under different levels offertilizer applications in 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.6.3 Effect of spacing on kernel per row under different levels of fertilizerapplications in 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.6.4 Effect of spacing on kernel per cob under different levels of fertilizerapplications in 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.6.5 Effect of spacing on test weight (1000 grain wt.) under different levelsof fertilizer applications in 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.6.6 Effect of spacing on grain yield under different levels of fertilizerapplications in 2, 3 and 5 years jhum cycles. Mean± SEM.

Table 5.6.7 Effect of spacing on Harvest Index (HI) under different levels offertilizer applications in 2, 3 and 5 years jhum cycles. Mean± SEM.

iv

LIST OF FIGURES

Fig. 3.1 Map of the districts in Mizoram State showing the location ofAizawl city.

Fig. 3.4 Map of Mizoram State showing open and dense forest. (ISFR, 2011)

Fig. 4.1 Location of the experimental site at Edenthar showing the treatmentplots of the experimental block.

Fig. 5.3.1 Effect of fertilizer application on plant height at 15 DAS under differentspacing in 2 years, 3 years and 5 years jhum cycles.




Fig. 5.3.5 Effect of fertilizer application on number of leaves per plant at 15 DASunder different spacing in 2 years, 3 years and 5 years jhum cycles.




Fig. 5.3.9 Effect of fertilizer application on biomass production at maturityharvest under different spacing in 2 years, 3 years and 5 years jhum cycles.

Fig. 5.4.1 Effect of fertilizer application on length of cob under different spacing in2 years, 3 years and 5 years jhum cycles.

Fig. 5.4.2 Effect of fertilizer application on kernel rows per cob under different spacingin 2 years, 3 years and 5 years jhum cycles.

Fig. 5.4.3 Effect of fertilizer application on kernels per row under different spacing in2 years, 3 years and 5 years jhum cycles.

v

Fig. 5.4.4 Effect of fertilizer application on kernels per cob under different spacing in2 years, 3 years and 5 years jhum cycles.

Fig. 5.4.5 Effect of fertilizer application on test weight under different spacing in2 years, 3 years and 5 years jhum cycles.

Fig. 5.4.6 Effect of fertilizer application on grain yield under different spacing in2 years, 3 years and 5 years jhum cycles.

Fig. 5.4.7 Effect of fertilizer application on harvest index under different spacing in2 years, 3 years and 5 years jhum cycles.

Fig. 5.5.1 Effect of spacing on plant height at 15 DAS under different fertilizerapplication levels in 2 years, 3 years and 5 years jhum cycles.




Fig. 5.5.5 Effect of spacing on number of leaves per plant at 15 DAS underdifferent fertilizer application levels in 2 years, 3 years and 5 yearsjhum cycles.




Fig. 5.5.9 Effect of spacing on biomass production at maturity harvest underdifferent fertilizer application levels in 2 years, 3 years and 5 yearsjhum cycles.

Fig. 5.6.1 Effect of spacing on length of cob under different fertilizer applicationlevels in 2 years, 3 years and 5 years jhum cycles.

Fig. 5.6.2 Effect of spacing on kernel rows per cob under different fertilizerapplication levels in 2 years, 3 years and 5 years jhum cycles.

vi

Fig. 5.6.3 Effect of spacing on kernels per row under different fertilizerapplication levels in 2 years, 3 years and 5 years jhum cycles.

Fig. 5.6.4 Effect of spacing on kernels per cob under different fertilizerapplication levels in 2 years, 3 years and 5 years jhum cycles.

Fig. 5.6.5 Effect of spacing on test weight under different fertilizer applicationlevels in 2 years, 3 years and 5 years jhum cycles.

Fig. 5.6.6 Effect of spacing on grain yield under different fertilizer applicationlevels in 2 years, 3 years and 5 years jhum cycles.

Fig. 5.6.7 Effect of spacing on harvest index under different fertilizer applicationlevels in 2 years, 3 years and 5 years jhum cycles.

vii

LIST OF PHOTOPLATES

Plate 1 Experimental site at Edenthar locality showing plot-wise demarcation.

Plate 2 Growth performance of different spacing and fertilizer applicationplots of 2 years jhum cycle.

Plate 3 Growth difference between S1F0 and S3F3 plots of 3 years jhumcycles at 30 DAS.

Plate 4 Mimpui maize of S2F3 plot (120:60:40 NPK kg/ha; 60cm x 25cmspacing) at 45 DAS in 5 years jhum cycle.

Plate 5 Taking growth measurement at 60 DAS on S2F2 plot of 5 years jhumcycle.

Plate 6 S1F0 plot (55cm x 20cm spacing; no fertilizer application) of 2 yearsjhum cycle at the same time of silking stage.

Plate 7 Cobs of Mimpui maize growth under S3F3 (75cm x 20cm spacing;120:60:40 NPK kg/ha application) in 5 years jhum cycles.

Plate 8 Weighing of harvested grains for measurement of grain yield per plantand test weight.

viii

LIST OF ABBREVIATIONS USED

oC : Degree Celcius

% : per cent

cm : centimeter

E : East

Ed: (eds.) : Edition: editor(s) or edited

et al. : et alii: and others

etc. : etcetera or cetera: and the others

g/gms : gram(s)

ha : hectare

K : Potassium

m : metrum: metre

mg : milligram

mm : millimetrum: millimeter

ml : milliliter

N : North / Nitrogen

no. : numero: number

p., pp. : pigina: page, pages

P : Phosphorus

qt : quintal

sp., spp : species (singular); species (plural)

ix

1

Chapter – I

INTRODUCTION

1.1 Global Agriculture production

Agriculture is the world’s largest use of land, occupying about 38% of

the Earth’s terrestrial surface. The agricultural community has had tremendous

successes in massively increasing world food production over the past five decades

and making food more affordable for the majority of the world’s population, despite a

doubling in population (Dobermann and Nelson, 2013).

Approximately 790 million people in developing countries are

described as undernourished, with Sub-Saharan Africa highlighted as the region

with the greatest hunger (<1260kJ/ day) affecting 180 million people (FAO, 2002).

Even more troubling is the fact that thousands die daily as a result of diseases from

which they likely would have survived had they received adequate food and nutrition

(Craig D. Idso, 2011). The number of undernourished increased in the rest of East

Asia (excluding China) and even more in the rest of South Asia (excluding India)

(FAO 2006).

By 2025, continuing population growth and current agricultural

practices will lead to 36 more countries (pop. 1.4 billion) falling into the category

currently occupied by 21 countries (pop. 600 million) where either good cropland or

fresh water are scarce (National Intelligence Council. 2008). Credible research

already makes it clear that there is a growing depletion of the key natural resources,

including land, water, and biodiversity, that are fundamental for sustainable

2

production. No human endeavour uses more of these resources than agriculture.

(OECD, 2011).

Of the world’s 1.1 billion extremely poor people, about 74 % (810

Million) live in marginal areas and rely on small scale agriculture. While the world

currently produces enough food to feed everyone, at least one billion people remain

food insecure (FAO, 2010). Although the incidence of hunger dropped from a ratio of

one in three in 1960 to affecting roughly one in seven people by the 1990s, the trend

reversed in the 1990s and the absolute number of people blighted by hunger continues

to grow. In 2009, for the first time in history the population considered to be

malnourished exceeded one billion people Sub-Saharan Africa has the highest

proportion of undernourished people, 30 percent in 2010, while the Asia Pacific

region has the most undernourished people (578 million) according to the FAO. Two

thirds of the world's undernourished live in just seven countries – Bangladesh, China,

the Democratic Republic of Congo, Ethiopia, India, Indonesia and Pakistan (FAO,

2010).

It is also estimated that by 2050 another 2.3 billion people will be

added to the current population of 7 billion, with most of this increase happening in

countries that are home to significant numbers of people suffering from food

insecurity, malnutrition, and extreme poverty (2010 Revision of World Population

Prospects. U.N. Population Division of the Department of Economic and Social

Affairs).

The Green Revolution made available a package of biochemical inputs

(HYVs, fertilizer and irrigation) that promised to be scale neutral and thus raise the

yields and incomes of all farmers and substantial Government subsidies allowed

3

increased production through crop intensification (Bernstein et al., 1992). While

there is little doubt that the Green Revolution enabled massive increases in yields

and the achievement of self-sufficiency in grains for India, it had a very uneven

impact on regions, crops, and individuals (Lipton and Longhurst, 1989). Rural people

take part in a number of strategies, including agricultural intensification, migration

and livelihood diversification, which enable them to attain a sustainable livelihood

(Tiffen et al., 1994).

Productivity increase has been particularly strong in developing

countries, and especially for cereals such as rice in Asia, wheat in irrigated and

favourable production environments worldwide, and maize in Mesoamerica and

selected parts of Africa and Asia (Pingali and Heisey, 2001). Most of the world

irrigated agriculture today is in developing countries. Nearly one half of the irrigated

area of the developing countries is in India and China. Food consumption, in terms of

kcal/person/day, is the key variable used for measuring and evaluating the evolution

of the world food situation (Alexandratos and Bruinsma, 2012). Food production is

particularly sensitive to climate change, since crop yields depend in large part on

climate conditions such as temperature and rainfall patterns (Stern, 2007).

The increased food production will also have to occur on less available

arable land and this can only be accomplished by intensifying production which must

be done in an environmentally safe manner through ecological intensification.

Commercial fertilizer is responsible for 40% to 60% of the world’s food production.

So, effective and efficient use of fertilizers is very important to increase the supply of

food demand (Roberts, 2009).

4

Future word populations will require ever-increasing food supplies.

The availability of food per capita has been declining for nearly two decades, based

on available cereal grains. Cereal grains make up 80% of the world’s food. Although

grain yields per hectare in both developed and developing countries are still

increasing, these increases are slowing while the world population continues to

escalate (PRB, 2002). Although agricultural productivity has generally increased

globally, it has hardly kept the pace with population growth. In much of the

developing world, population growth has negatively impacted food security.

(Ramankutty et al., 2002).

Grains such as rice, wheat, and maize account for about half of human

caloric intake (FAO. 2002). About half of the world’s grain is now used to produce

animal feed and animal consumption is projected to double between 2000 and 2050

(Steinfield et al., 2010). A change in the availability of grains has an effect on the

food available for a large part of the human population (Yotopoulos, 1985). The vast

majority of the world’s farmers are smallholders and small farms are at risk. A trend

toward the dominance of larger farms is occurring in some countries even as

fragmentation and population growth is leading to ever smaller and perhaps

unsustainable farms in others.

Agricultural growth contributes directly to food security. It also supports

poverty reduction. The population increase, combined with moderately high income

growth, could result in a more than 70% increase in demand for food and other

agricultural products by 2050. Much of this growth originated in developing countries

(3.4 – 3.8 percent p.a.). Even though the value of total agricultural output per capita

5

has had a yearly growth of 0.6% p.a. since 1961, not all regions have followed the

same trend (Wik et al., 2008).

A trend of increasing urbanization is detected worldwide (Mitlin,

2005) which is proceeding at a high pace is an important factor influencing

consumers’ preferences (MEA, 2005). This affects food consumption patterns in a

number of ways (Regmi and Dyck, 2001). Globally, urbanization is expected to

double the proportion of urban residents to the total population, reaching nearly four

billion by 2020 and affecting mainly developing countries (Haddad et al., 1999;

Regmi and Dyck, 2001). Global trade in food and feed crops has accelerated over the

period (Galloway et al., 2007) and higher income levels are associated with a greater

demand for more expensive sources of calories, such as meat, fruit, vegetables, and

processed food products (Seale et al., 2003)

1.2 INCREASE IN AGRICULTURAL LAND AND ITS EFFECTS ON

DEFORESTATION

Forests cover almost one third of the earth’s land surface

providing many environmental benefits including a major role in the hydrologic cycle,

soil conservation, prevention of climate change and preservation of biodiversity

(Sheram, 1993). Deforestation including clearing for agricultural activities is often the

only option available for the livelihoods of farmers living in forested areas (Angelsen,

1999). A global move to sustainable agriculture for sustainable development is clearly

vital (Munasinghe and Swart, 2005). Land conversion from forests to agriculture and

pasture has been associated with climate changes at the global scale (Fearnside,

1996). While developed countries have contributed to much of the planet’s recent

6

warming trend by burning fossil fuels and via the introduction of industrial

compounds. Adger and Brown (1994) estimated that tropical deforestation is

responsible for between 25% and 30% of the purported climate warming in the world;

and forests are responsible for about 90% of the carbon stored in global vegetation

(Dale, 1997). Furthermore, climate change is believed to affect world food supply and

productivity (Brown, 1994).

The practice of jhum cultivation is reported to account for 60%

forest losses worldwide each year (Lele et al., 2008). The ever increasing population

has created tremendous pressure on land to provide basic requirement for survival. To

meet these requirements, the limited natural resources are being over-exploited

resulting in widespread ecosystem degradation (Grogan et al., 2012). Grazing land

and land for crops to feed animals, makes up 80% of all agricultural land – 3.4 billion

hectares for grazing and 0.5 billion hectares for feed crops (FAO, 2009). Forests are

often cleared to make space for this grazing and feed crop land; over the last 25 years,

the world has lost forests equal in size to India (FAO, 2006).

The impacts of population pressure on land degradation may be mixed.

Land degradation may increase as a result of cultivation on fragile lands, reduced use

of fallow, increased tillage, mining of soil nutrients, and other potential results of

intensification. On the other hand, investments in land improvements and more

intensive soil fertility management practices may improve land conditions (Pender,

2001; Tiffen et al., 1994; Scherr and Hazell, 1994).

It is generally agreed that agricultural impacts will be more adverse in

tropical areas than in temperate areas (Parry et al., 2005; Fischer et al., 2005), and that

climate change effects will likely widen the gap between developed and developing

7

countries. Low levels of warming in temperate areas (US, Europe, Australia and some

parts of China) may improve the conditions for crop growth by extending the growing

season and/or opening up new areas for agriculture. But further warming will have

increasingly negative impacts, as damaging temperature thresholds are reached more

often and as water shortages limit crop growth in semi-arid regions such as Australia,

Southern Europe and Western USA (IPCC, 2007).

Deforestation is primarily a concern for the developing countries of the

tropics (Myers, 1994) as it is shrinking areas of the tropical forests (Barraclough and

Ghimire, 2000) causing loss of biodiversity and enhancing the greenhouse effect

(Angelsen et al., 1999). The relationship between development and deforestation is

complex and dynamic (Sands, 2005; Humphreys, 2006). Deforestation is the

conversion of forest to an alternative permanent non-forested land use such as

agriculture, grazing or urban development (Kooten and Bulte, 2000). Rowe et al.,

(1992) estimated that 15 per cent of the world’s forest was converted to other land

uses between 1850 and 1980. Deforestation occurred at the rate of 9.2 million

hectares per annum from 1980-1990, 16 million hectares per annum from 1990-2000

and decreased to 13 million hectares per annum from 2000-2010.

Indeed, it is feared that agricultural expansion which is the main cause

of deforestation in the tropics might replace forestry in the remaining natural forests

(Anon., 2002; Cossalter and Pye-Smith, 2003; Anon., 2005). The impact of timber

plantations could thus turn out to be quite detrimental to tropical forest ecosystems

(Kartodihardjo and Supriono, 2000). Based on the data available from 118 countries

representing 65 per cent of the global forest area, an average of 19.8 million hectares

or one per cent of all forests were reported to be significantly affected each year by

8

forest fires (Anon., 2010). Although small farmers and shifting cultivators are not the

main drivers of deforestation in regions where most deforestation takes place, they do

contribute to it. In the long run, reducing their impacts on deforestation might be more

difficult than reducing deforestation from large-scale commercial agricultural or

logging operations (Shearman et al., 2009). On the other hand, it may be more

difficult to develop the new systems that ensure small farmers and shifting cultivators

retain their livelihoods without additional deforestation.

Expanding cities and towns require land to establish the infrastructures

necessary to support growing population which is done by clearing the forests (Sands,

2005). Tropical forests are a major target of infra-structure developments for oil

exploitation, logging concessions or hydropower dam construction which inevitably

conveys the expansion of the road network and the construction of roads in pristine

areas (Kaimowitz and Angelsen, 1998). The demands of urban populations lead to

farmland expansion in rural forested areas to produce more crops, which impact

forest conversion for agriculture and lead to deforestation (Carr et al., 2006).

Agricultural land expansion is generally viewed as the main source of deforestation

contributing around 60 per cent of total tropical deforestation (Wilkie et al., 2000;

Amor, 2008; Amor and Pfaff, 2008). Increasing agricultural yields has been the

predominant mode for increased food production for the last several decades, but

intensification can also lead to more deforestation in some circumstances (Rudel et

al., 2009;Boucher et al., 2011).

Research published in 2012 estimates that agriculture is estimated to be

the direct driver of 80% of the world’s deforestation. According to the Millennium

Ecosystem Assessment (MEA), the most important drivers of biodiversity loss are

9

habitat change, climate change, invasive alien species, overexploitation, and pollution.

These include the clearing of land for crops and the use of fossil fuel-based and often

toxic pesticides and fertilizers that pose risks to human health and wildlife

populations. (Brighter Green and GFC, 2013).

Most of the causes of deforestation, including logging, land conversion

to agriculture, wildfires, cutting down trees for firewood, and conflict over land rights

tend to be caused by increased population growth and a need for more land mostly

for agricultural production (Johnson and Chenje, 2008). The highest rates of

deforestation (in 106 ha/yr during the 1990s) occurred in Brazil (2.317). India (1.897),

Indonesia (1.687), Sudan (1.003), Zambia (0.854), Mexico (0.646), the Democratic

Republic of the Congo (0.53; b7b8), and Myanmar (0.576) (FAO, 2001).

Ecological research is leading to new understanding of agro-ecosystem

function that is enabling yield growth through improved nutrient cycling, water

utilization, improved pest and disease management, nitrogen fixation, and synergistic

plant interactions (IAASTD, 2010). The World Resources Institute estimates that

only about 22% of the world's (old growth) original forest cover remains "intact".

Slash-and-burn techniques are used by native populations of over 200 million people

worldwide. Thus, solutions to deforestation must include and benefit local

communities. Community forestry involves a group of people practicing sustainable

management of forests; social and economic benefits to them are a central goal.

Intensification of small-scale agriculture can also reduce agricultural expansion into

forested areas if the correct incentives are in place (Palm et al., 2010).

Jhum cultivation is considered as a major driver of deforestation.

Globally, until the year 1991, jhum had accounted for 61% of overall tropical forest

10

destruction (Myers, 1991). Nevertheless, the practice persists since it provides

subsistence livelihoods to at least 300 to 500 million people worldwide (Brady, 1996)

and is intricately linked to cultural, ecological, and economic aspects of communities

(Ramakrishnan, 1992). While certain ecologists question the sustainability of the

practice, since it involves clearing of primary and secondary forests, others appreciate

the existence of the practice for several millennia and acknowledge the fact that

timber-felling, monoculture plantations (Dressler, 2005; Ickowitz, 2006) and other

such economic-oriented objectives are also critical drivers of deforestation. However,

when fallow cycles drop below a critical time period due to increased human

population leading to unavailability of land, the productivity of the plot as well as

forest regeneration are negatively affected (Raman et al, 1998). The density of human

population jhum can sustain is 7 km-2, which is considerably lower than present

densities in Jhum landscapes in the tropics (Whitmore, 1984).

1.3 JHUM CULTIVATION

Jhum cultivation is one of the most ancient system of farming

(Borthakur, 1992) believed to have originated in the Neolithic period around 7000

B.C. (Spencer, 1966). The system is regarded as the first step in transition from food

gathering and hunting of food production. It is practiced in different parts of the

world. It is a multifaceted form of agriculture has been widely practiced by hill

communities in Asia, Africa, and Latin America since 13,000 to 3,000 B.C. (Mazoyer

and Roudart, 2006). The cropping system encompasses horticulture, annual/perennial

crops, animal husbandry and management of forests and fallows in sequential or

rotational cycles (Thrupp et. al., 1997).

11

In the Jhum system of cultivation a piece of forest land is slashed,

burnt and cropped without tilling the soil, and the cropped land is subsequently

fallowed to attain pre-slashed forest status through natural succession (Uhl et al.,

1983; Ramakrishnan, 1993). It is an old-age practice among the tribal groups

throughout the tropic- the Amazon basin, Southeast Asia and Sub-Saharan Africa. It is

largely viewed as an exploitative system, where the land and natural resources are not

managed.

The cultivation, typically involves clearing the land, burning much of

the plant material, planting and harvesting crops, and then abandoning the land for

fallow and moving to new plot of land. During the fallow period, the forest vegetation

re-grows and can be re-burned at a later date, adding nutrients to the soil for future

cropping (Teegalapalli et al, 2009). The intervening period for which a jhum land is

abandoned is known as jhum cycles (Bam, 2015). It is called by different names in

different parts of the world. It is generally known as ‘slash and burn’ and ‘bush

fallow’ agriculture. It is variously termed as Ladcmg in Indonesia, Caingin in

Philippines, Milpa in Central America and Mexico, Ray in Vietnam, Conuco in

Venezuela, Roca in Brazil, Masole in the Congo and Central Africa (Priyadarshni,

1996).

Jhum cultivation is the key to the livelihoods of many ethnic,

indigenous and tribal groups in the tropical and sub-tropical regions (Andersen et al.,

2008). In many places in the tropics, traditional jhum cultivation is practiced by

indigenous peoples who have inhabited remote forest areas for a long time, whereas

migrant farmers living at the forest edge may be practicing small scale slash-and-

burn-agriculture without incorporating long fallow periods (Sanchez et al., 2005). The

practice of jhum is not, merely exercised by the tribals for their sustenance, but a

12

traditional method of earning a livelihood, a traditional farming system that uses local

product and techniques, has rooted in the past, has evolved to their present stage as a

result of the interaction of the cultural and environmental condition of the region and

is deeply embedded in the tribal psyche (Gupta, 2005).

1.4 JHUM CULTIVATION – GLOBAL SCENARIO

Throughout the world there are about 70 million people living in

remote tropical forests (Chomitz et al., 2007). Across South and Southeast Asia a

large number of people depend for their livelihood and food security fully or partly on

jhum cultivation. The actual number of these people is not known. The number of

jhum cultivators in Southeast Asia has been estimated to lie between 14 and 34

million people (Mertz et al., 2009).

Jhum cultivation is probably one of the most misunderstood and

controversial forms of land use. In 1957, the FAO declared jhum cultivation the most

serious land use problem in the tropical world (FAO, 1957). The majority of the

people practicing jhum cultivation in South and Southeast Asia belong to ethnic

groups that are generally subsumed under categories like ethnic minorities, tribal

people, hill tribes, aboriginal people or Indigenous Peoples (Erni, 2008). In South

Asia, this cultivation is practiced particularly by Adivasis in Central and South India

and by indigenous peoples in the Eastern Himalayas, i.e. Eastern Nepal, Northeast

India, the Chittagong Hill Tracts of Bangladesh and the adjacent areas across the

border in Myanmar. In mainland Southeast Asia, jhum cultivation has until very

recently been the predominant form of land use in all the mountainous areas. The

same holds true for the remote interior and uplands of Insular Southeast Asia (Cramb

et al., 2009).

13

Jhum cultivation throughout the tropics is largely a subsistence activity

practiced in areas with few alternative options and is therefore a practice that is likely

to continue. Secondary forests formed following logging and jhum cultivation covers

more than 600 million hectares and play an important role in biodiversity

conservation in the tropics (Brown and Lugo, 1990). Since jhum cultivation in the

tropics is mainly practiced on nutrient-poor soils, forest vegetation re-growth and re-

burning is important for crop growth. Furthermore, weed, pest, and crop disease

populations decline. Fallow periods in a jhum cultivation system vary and can be long

enough for forests in abandoned plots to regenerate. The cultivation can imply a

diverse set of farming practices, and in some cases fallow land is partially planted

with tree crops for subsistence use or additional income. Many jhum cultivators are

semi-subsistence and small-scale farmers in tropical rainforest areas (Mertz et al.,

2009; Hassan et al., 2005; Giller and Palm, 2004).

Nearly in the past ten years, fewer jhum cultivators can allow for long

fallow periods and regeneration of forests because they do not control large enough

areas due to population densities, political pressures, and economic demands in

tropical regions. The historical system of jhum cultivation, which can be sustainable

in areas with low population densities and large land areas, is rare and has mostly

been supplanted by agricultural intensification (Chomitz, 2007; Sanchez et al., 2005).

Small-scale farmers cultivate many types of crops depending on the

region. For tropical regions broadly, some of the most important cereals grown for

food include grains like rice, maize, sorghum, and millet. Cassava, sweet potatoes,

and bananas are also important foods (Norma, Pearson, and Searle 1984). Women

14

play a major role in small-scale agriculture, particularly in Sub-Saharan Africa, where

they make up the majority of farmers. (Mehra and rojas 2008; World Bank, 2007).

In many parts of Southeast and South Asia, jhum cultivators are

currently confronted with a resource crisis as the population-land ratio has reached

critical levels. Population growth, caused by natural growth and spontaneous in-

migration and resettlement, is however only one of its causes (Cramb et al., 2009).

Government restrictions on jhum cultivation and large-scale alienation of Indigenous

Peoples’ land have in many cases been the main cause of land scarcity. However,

against predictions by concerned policy makers and environmentalists, the crisis did

not lead to collapse and shifting cultivators have adapted by modifying their

livelihood and land use practices (Padoch, et al., 2007).

There are underlying reasons for the actions of small farmers and jhum

cultivators. Road and infrastructure development in tropical forest regions has given

migrant farmers access to previously inaccessible forest areas. In some regions,

poverty-driven deforestation can occur if small-scale and subsistence farmers lack

resources or secure land tenure and are forced to move into forested areas to grow

food and earn their livelihoods (Sanchez et al., 2005; geist and lambin 2002).

Small-scale subsistence farmers with little connection to markets

deforest less, highlighting the importance of commercial markets and urban and

international demand as underlying causes of deforestation (deFries et al., 2010;

Pacheco, 2009). In the past seven years, government-sponsored colonization programs

facilitated the movement of landless migrants to the frontiers of tropical forests

(Sanchez et al., 2005; Rudel et al., 200;). In the 1960s and 1970s, the cold war and the

Cuban revolution encouraged rural movements for land reform in Latin America and

15

Southeast Asia. Governments responded with colonization programs to provide small

farmers with land in remote forested regions, since this was easier than taking land

away from large farmers. In order to help this colonization effort, governments built

roads into rain forests. With the fall of the Soviet union and the end of the cold war,

this motivation for state-initiated deforestation disappeared (Rudel et al., 2009).

The international policy known as redd+ (reducing emissions from

deforestation and forest degradation, plus related pro-forest activities) can place value

on standing forests and provide economic incentives for (a) reducing carbon dioxide

emissions resulting from deforestation and (b) increasing sequestration of carbon

through forestry practices. In these programs, establishing land tenure and other

entitlements for small farmers, indigenous peoples, and other stakeholder groups such

as women is important for the inclusion of small farmers in a redd+ system. Such

international policies can benefit jhum cultivators and small-scale farmers if

structured correctly and equitably (Mertz, 2009).

In many parts of Southeast and South Asia, shifting cultivators are

currently confronted with a resource crisis as the population-land ratio has reached

critical levels. While natural growth of local populations has contributed to increasing

land scarcity, state-sponsored or spontaneous in-migration and resettlement are the

more common cause (Cramb et al., 2009). Fox et al., (2009) have identified six

external factors that contribute to the profound transformation or complete

replacement of jhum cultivation:

1. Classifying shifting cultivators as ‘ethnic minorities’ in the course of nation

building, and the concomitant denial of ownership and land-use rights;

16

2. Dividing the landscape into forest and permanent agriculture, the claim over the

former by forest departments and the transfer of use rights to logging companies and

commercial plantations;

3. The expansion of forest departments and the rise of conservation, which have

further expanded and strengthened state control over forests;

4. Resettlement of shifting cultivators out of upland and forest areas and the

dispossession of their lands as a result of the non-recognition of collective or

individual rights over land and forests;

5. Privatization and commoditization of land and land-based production, resulting in

dispossession of shifting cultivators and giving rise to commercial agriculture and

industrial tree-farming by private companies, state enterprises as well as

entrepreneurial farmers and small-holders;

6. Expansion of infrastructure (roads, electricity, telecommunication) and subsidies

for investors supporting markets and promoting corporate and private industrial

agriculture.

It is too obvious that there are simply not enough resources for all

countries to become as industrialized and reach the level of consumption of natural

resources as Europe or the United States. According to Tudge (2005), “Only

agriculture can employ the vast numbers of people who need employment. Only

agriculture can do so sustainably.” Thus, many people will continue to directly live

off the land, indigenous peoples in particular.

Urbanization and population pressure are the two most important

threats to biodiversity worldwide and their growth affected natural resources. Urban

area may make threats ecosystem through direct habitat conversion (Clergeau et al.,

1998; McKinney, 2002) and through various indirect effect of human population

17

pressure like resource use, habitat fragmentation, waste generation and fresh water

cooption (Mikusinski and Angelstam, 1998). Understanding the complex mechanism

of biodiversity necessitates its spatial and temporal dynamics management of

landscape and synergetic adoption of measurement approaches with long-term plot

inventories are imperative (Yadav et al., 2012).

Due to increase of population density many kind of precursor, both

social and environmental, appears in habitat. One environmental precursor is

pollution, the effect of which in forest ecosystem studied by many investigators

(Bormann and Likens, 1979). The other is population pressure which is caused by

excessive increase in population density in forest habitat leading to argumentation of

industrialization and consumption of natural resources for livelihood. Increasing

human intervention and excessive exploitation of resources have resulted in great

changes and provide alarming signals of accelerated biodiversity loss (Yadav et al.,

2013). The impact of population growth on environment is significant because each

person make same demands on natural resources for the essential of life-food, water,

clothing, shelter and so on.

1.5 JHUM PRACTICE IN INDIA

About 10 million hectare of tribal land stretched across 16 states

estimated to be under jhum cultivation in India (Eswaraiah, 2003) which is about 0.32

percent of total geographical area. On an average, estimated 38.69 thousand hectare

area is set under this type of cultivation every year (Tripathi and Barik, 2003) and

nearly 600,000 families are involved in jhum cultivation all over India (Keitzer,

2001). There are varieties of livelihood practices by the tribal communities in

18

different parts of India and elsewhere, such as the hunter-gatherers, pastoralist and

jhum cultivators who live in different environments. Many changes have been taking

place with regard to land use, access, control and utilization of their resource and

these changes in turn have largely affected the sustainable livelihoods of the people

without emphasizing sustainable replacement (Shivaprasad and Eswarappa, 2007).

In India, Green Revolution started in the 1960s based on use of commercial

fertilizer and pesticides along with novel crop strains developed using genetics and

biotechnology (Mooney et al., 2005), has made the country self sufficient for

nourishing the growing populations. However, this agricultural intensification has

negative impact on the soil fertility and thus there is a plateau formation in Indian

agriculture production. Maintenance of soil organic matter is a major problem in

sustained high crop production practices and environmental contamination in Indian

agriculture (Kushwaha et al., 2000, 2001; Kaufman and Watanasak, 2011).

This cultivation practice has different names in India. It is known as

Jhum in the hilly states of Northeast India, as Podu, Dabi, Koman or Bringa in Orissa,

as Kumari in Western Ghats, as Watra in southeast Rajasthan, as Penda, Bewar or

Dahia and Deppa or Kumari in the Bastar district of Madhya Pradesh (Priyadarshni,

1996). Indian Agricultural sector has been undergoing astonishing changes since

1950s. The record production of food grains from 50 million tons in 1950 to 241

million tons in 2009-10 is hailed as a breakthrough in Indian agriculture (Anonymous,

2011).

In India, the people of eastern and north-eastern region practice jhum

cultivation on hill slopes. 85% of the total cultivation in northeast India is by jhum

cultivation (Singh and Singh, 1992). Due to increasing requirement for cultivation of

19

land, cycle of cultivation followed by leaving land fallow has reduced from 25–30

years to 2–3 years. Earlier the fallow cycle was of 20–30 year duration, thereby

permitting the land to return to natural condition. Due to reduction of cycle to 2–3

years, the resilience of ecosystem has broken down and the land is increasingly

deteriorating (Patro and Panda, 1994). The degree of soil degradation depends on

soil’s susceptibility to degradative processes, land use, the duration of degradative

land use, and the management. Soil and water degradation are also related to overall

environmental quality, of which water pollution and the greenhouse effect are two

major concerns of global significance. Recent global concerns over increased

atmospheric CO2, which can potentially alter the earth’s climate systems and have

resulted in raising interest in studying soil organic matter (SOM) dynamics and

carbon (SOC) sequestration capacity in various ecosystems (Schlesinger, 1999).

1.6 JHUM CULTIVATION IN NORTH EAST INDIA

Geographically, North East (NE) India stretches between 21°50’ and

29°34’ N latitude and 85°34’ and 97°50’ E longitude. This region is covering a

geographic area of 2,55,143 sq km and holding a population of 38 million, which are

8% and 3.85% of area and population of whole India, respectively. Most marked

characteristics of this region are large rural population (89.86%), huge tribal

inhabitants (Irshad Ali and Das, 2003) and wide area covered under forests (63.9%)

(Mishra and Sharma, 2001). The region is characterized by diverse agroclimatic and

geographical situations (Borthakur, 1992).

“Jhum”, a shifting agriculture technique pertaining to North-Eastern

Region of India (NERI) is traditionally being practiced by local tribes from ancient

20

ages (Deka and Sarma, 2010). The North Eastern Region comprises the contiguous

seven sister States (North-east India) - Arunachal Pradesh, Assam, Manipur,

Meghalaya, Mizoram, Nagaland Tripura and the Himalayan state of Sikkim. In all of

north-east states, an estimated 1466 thousands hectares of land are under jhum

cultivation (Yadav, 2013) which contributes 85% of the total cultivation in Northeast

India. About 26,000 households practice Jhum cultivation every year and nearly

143,000 people depend on it for subsistence (Shoaib, 2000). In fact, whole of NERI

can be appropriately termed as the land of jhum cultivators and the cultivation area

practiced in this region is nearly 19.91 lakh ha and it is approximately 83.73% of the

total jhum cultivation area in India (GOI, 2000; Mandal, 2011). It has evolved as a

traditional practice and is an institutionalized resource management mechanism

ensuring ecological sustainability and food security thus providing a social safety net

for local communities (Andersen et al., 2008).

Jhum cultivation is a unique feature of agriculture in the hilly region

of NE India. Although, this practice is criticized due to low productivity and

environmental diseconomies; continuance of jhum cultivation is closely linked to

ecological, socio-economic, cultural identity and land tenure systems of tribal

communities (Deka and Sarmah, 2010). The low productivity is due to many

limitations viz. prevalence of jhum cultivation, hilly terrain, unpredictable climate

changes, low levels of modern input use, poor infrastructure etc. (Karmakar, 2008;

Barah, 2006). This cultivation in some form or other is still in vogue as a whole in

NERI and is being extensively practiced by more than 100 tribal ethnic minorities

(Singh et al., 1996; Ramakrishnan, 1993). The selection of land is made in the months

of December and January by the village elders or clan leaders.

21

In some tribes, community as a whole is collectively responsible for

the clearing of the selected piece of land while in others the cutting of trees and shrubs

is made by the respective family to whom the land has been allotted. At the time of

allotment of land the size and workforce in the family are taken into consideration.

The Jhumias adopt mixed cropping. The mixture of crops varies from tribe to tribe

within a region. About 35 crops are cultivated in a jhum cultivation system

(Arunachalam et al., 2002). The jhum cultivators grow food grains, vegetables and

also cash crops. In the mixed cropping, soil exhausting crops, e.g., rice, maize,

millets, cotton, etc., and soil enriching crops, e.g., legumes, are grown together. In

fact, the grower aims at growing in his jhum land everything that he needs for his

family consumption. In other words, the choice of crop is consumption oriented

(Priyadarshni, 1996).

With the phenomenal increase in human population the jhum cycle has

been increased from 20 to 30 years in the past to about 5 years and in many areas even

up to 3 years (Toky and Ramakrishnan, 1981; Singh et al., 1996). The system

involves cultivation of crops in steep slopes (Borthakur, 1992). Nearly 57.1% of total

geographical area (TGA) in India is under the threat of land degradation mainly by

water erosion. On an average, 37.1% of TGA in NE India is in degraded state. Due to

short fallow cycles in north-east India resulted in arrested succession, since weedy

species were not succeeded by pioneer woody species, and over time the soil seed

bank was replaced with seeds of weedy shrubs. Fallows as old as 10 years in the

region were dominated by bamboo cover (Raman et al., 1998). However, early

colonizers such as bamboo, with relatively faster growth rates in comparison with

woody tree species, may have facilitated soil-nutrient recovery and provided

microhabitats for regeneration of shade-loving species. The net change in soil

22

available nutrient pool from pre-cropped stage through slashing and burning and

subsequent cropping result in substantial lowering of carbon, nitrogen and magnesium

(Das et al., 2012).

The continuance of jhum in the north-east states is closely linked to

ecological, socio-economic, and cultural and land tenure systems of tribal

communities. Since the community owns the lands, the village council or elders

divide the jhum land among families for their subsistence on a rotational basis (Rao

and Ramakrishnan, 1989). On an average, 3,869 km2 area is put under jhum

cultivation every year. Jhum cultivation in its more traditional and cultural integrated

form is an ecological and economically viable system of agriculture as long as

population densities are low and jhum cycles are long enough to maintain soil fertility

(Tawnenga et al., 1996).

Slash-and-burn land clearing on sloping land may lead to increased soil

run-off following disappearance of the protective vegetative cover. In turn, soil run-

off and redeposit ion affects soil fertility and spatial patterns of fertility parameters in

a field. Soil erosion is an irreversible phenomenon causing land degradation and

deterioration of surface water quality. Soil degradation is responsible for making 0.3-

0.8% of the world’s arable land unsuitable for agricultural production every year and

an additional 200 million ha of cropped area would be required over the next 30 years

to feed the increasing population (Biggelaar et al., 2004; Lafond et al., 2006).

The jhum cultivation adversely affects eco-restoration and ecological

process of forests and this leads to degradation of land causing soil erosion and finally

converting forests into wastelands (Dwivedi, 2001). This cultivation practices cause

23

tremendous loss of soil nutrients (Shahlace et al., 1991) and degradation of natural

vegetation (Nair and Fernandes, 1984) whereas, this loss can be minimized to almost

negligible level by managing the watersheds (Sahoo et al., 1993). The intensity of

jhum cultivation practices leads to low rainfall due to destruction of habitat reduces

biological diversity and extinction of previously undiscovered indigenous species too.

Jhum cultivation causes large-scale damage to the forests and has resulted in

deforestation and denudation of hill slopes, exposure of rocks due to soil erosion,

heavy silt loading on riverbeds and drying of perennial water resources (Goswami,

1968). Short Jhum cycle makes the land unsuitable for agriculture and leads to

considerable loss of soil nutrients through run-off and leaching (Borthakur et al.,

1979).

Land degradation in the region is 36.64% of the total geographical

area, which is almost double than the national average of 20.17% (Anon. 2000).

Burning of above-ground vegetation showed an increase in pH and cations and a

decrease in carbon and nitrogen contents in the surface soil (Ram and Ramakrishnan,

1988). Quick release of nutrients especially cations after burning has been reported by

Kellman et al., (1985). Fire is often responsible for large nutrient losses due to

particulate movement off the field and volatilization during the fire However, there is

a clear need for strengthening and improvement in other cases. Strengthening rather

than replacement of jhum cultivation is recommendable, especially considering the

benefits jhum cultivation has to offer (Yadav, 2013).

.Jhum cultivation practices deteriorate the soil fertility due to huge soil

loss of about 2200 t ha-1 yr-1 (Singh and Singh, 1978). A minimum period of 10 to 15

years is very much essential to maintain the soil fertility for sustainable crop

production (Singh et al., 2003). Carbon and Nitrogen in the soil may be among the

24

most limiting factors for plant growth after a forest is cut and then burned. Mishra et

al., (2003) reported that only fallow periods under jhum cultivation is not enough for

consideration of the restoration capacity of soil. The proper ratio of cropping and

fallow should be considered for sustainable Jhum cultivation.

Although, this practice is criticized due to low productivity and

environmental diseconomies; continuance of jhum cultivation is closely linked to

ecological, socio-economic, cultural identity and land tenure systems of tribal

communities there (Deka and Sarmah, 2010). The land-to-person ratio for the NE

region (0.68 ha person-1) is much higher than the national average (0.32 ha person-1)

(Anonymous 2011a). Although, NERI continues to be a net importer of food grains as

despite covering 8.8% of the country’s total geographical area, it produces only 1.5%

of the country’s total food grains production. Further, it was also noted that there was

gradually decrease in net land per family in jhum cultivation and increase in

permanent agriculture land per family from 1.10 to 0.7 and 0.35 to 0.74 ha family-1

respectively (Anonymous 2009). Despite diversification of their economic activities,

Jhumias earn meager income from jhum cultivation. Over last decade, the crop

productivity has been declined to 50% even after using fertilizers and pesticides to

some extent due to land and forest degradation (Mantel et al., 2006). Yields are

almost equal to input values and farmers are facing food shortage of 2 to 6 months

every year (Rezaul Karim and Mansor, 2011).

Application of fertilizers and plant protection chemicals has been

reported negligible in jhum cultivation and their use is also very limited in NERI

(Dewangan et al., 2004). In NERI, economy is primarily agricultural which

contributes about 30% to gross domestic product. At least 100 different indigenous

25

tribes and over 620,000 families with their own languages and cultural characteristics

inhabit here. They mainly depend on Jhum cultivation for their subsistence

(Ramakrishnan, 1992). In fact, Jhum cultivation is an ideal solution for agriculture in

humid tropics, as long as the human population density is low and fallow periods are

long enough to restore soil fertility (Watters, 1971).

Main indicators of poor agricultural growth in NERI include

prevalence of traditional agricultural practices, low level of mechanization, small size

of operational holdings, high vulnerability to natural calamities and degradation of

prime agricultural land and poor irrigation (Barah, 2006). Geophysical conditions

limit horizontal expansion of cultivable land (Shaheen et al., 2009; Barah, 2006). As a

result, the region is not able to produce adequate food grain to feed its own population

(Mishra and Misra, 2006). Under these circumstances, innovative strategy for

improving input usage is indeed an indispensable condition for increasing agricultural

production with safety and wellbeing of farmers.

Several rehabilitation schemes have been implemented by the state and

central governments to control jhum cultivation such as Watershed Development

Projects, Soil conservation schemes, Jhum Control Projects, New Land Use Policy

Scheme etc. (Tripathi and Barik, 2003). Farmers have a number of constraints,

problems or obstacles to switching over from jhum to settled agriculture such as lack

of adequate capital for investment, lack of irrigational facilities and non-suitability of

land for settlement (Patnaik, 2008). Traditionally, only a small amount of attention

has been given to the operator’s capabilities and limitations in the design of

agricultural hand tools and equipment in northeast India due to lack of proper

26

anthropometric and strength data bases of local people (Dewangan et al., 2010;

Agrawal et al., 2010).

1.7 JHUM CULTIVATION IN MIZORAM

Jhum cultivation is the most important and predominant mode of

raising food for forest farmers in Mizoram, north-eastern India. As much as 2 lakh

hectare land is affected by jhum, with approximately 63,000 ha being cultivated in a

given year by 50,000 families (Anonymous, 1987). The average jhum land per family

is about 1.3 ha and the present jhum cycle is four years (Anonymous, 1987).

According to the report of the Department of Rural Development in Mizoram, 80% of

the population resides in the recognized villages. Hence, forest constitute the most

important resource of the state, which covers 18,338 Sq. Km representing 86.99%

out of total geographical area of 21081 Sq. Km. Forest resources include agriculture

land, housing materials, firewood, medicine and food products (Anonymous, 2006).

Cropping on jhum lands in Mizoram is predominantly practiced for one year. The

second year cropping is scarce, and whenever done, is only on old jhum fallows. Even

in other parts of north-eastern India, the land is oft abandoned after first year of

cropping, and second year cropping is sometimes practiced with plantations of banana

and pineapple (Kushwaha and Ramakrishnan 1987).

However, farmers' apprehension that the yields obtained from the

second year of cropping are far lesser than those obtained from cropping new areas, is

not tested scientifically. While arguing about reduction in yield during second year

cropping the farmers do not take into account the energy invested in slashing and

burning newer areas every year, since energy in form of human labour is free for

27

them. The natural vegetation of Mizoram is a typical of "East-Himalayan subtropical

wet hill forests" at high altitude and "tropical wet evergreen forests" at low altitude.

About 75% of total geographical area is under forest cover (Champion and Seth,

1968).

Ecosystem productivity though increased consequent to fertilizer

application both in young and old fields, the per cent increase in young field was

almost twice that of old field. This result indicates that the young field exhibits greater

fertilizer use efficiency. Tilling is not much useful for improving either ecosystem

productivity or economic yield. Inorganic and organic manuring in isolation and in

combination respond differently; while inorganic manuring has greater impact on

ecosystem productivity, a combination of inorganic and organic manuring is more

suitable to improve economic yield during second year cropping (Tawnenga et al.,

1996).

The farmers continue the practices of jhum cultivation on the current

sites for a few years and then agricultural fields are abandoned. They shift their

agricultural fields to the other forest area. After few years gap, they again come back

to the previous fields. Mizoram is economically backward region. Its economy is

mainly dependent on the traditionally cultivating cereal crops. About 80% people are

engaged in agricultural practices. Rice is the main food-grain. The total consumption

of rice in Mizoram is 1,80,000 MT whereas, it produces only 44,950 MT rice (25%)

(Sati and Rinawma, 2014).

Mizoram is an extremely rugged mountainous region richly endowed

with forest resources. The economy of the state is primarily agriculture with majority

of the population (52%) practicing jhum (Shifting cultivation). In the past, the main

28

crops were rice, maize, millets and other cereals. Lately, there has been a significant

shift, with cereal crops being replaced by vegetables cash crops.

The 1990 Progress Report of Forestry in Mizoram stated that with the

increase in population and the need for bringing in more and greater areas under jhum

cultivation and urbanization for development, extensive areas have been deforested

with the result that forests are now confined mainly to reserve forests and patches of

areas not fit for agriculture (Anon., 1990). To replace jhumming, the government

introduced a number of policies such as horticulture, terracing and small scale

industries and New Land Use Policies (NLUP) between 1990 and 1996, the

government spent over Rs. 132 crores to 41,000 beneficiaries (Anonymous, 1996a).

Despite these efforts, the practice of jhum agriculture remained more or less the same.

Unlike the previous discourse, a new discourse on jhum was brought which discussed

how commercial tree plantations, fuel wood, and logging for timber extraction can

also have negative impacts on forest (Singh, 1996). Furthermore, alternative systems

introduced by the government are not always accepted by the local people (Singh,

1996).

The practice of jhum has an in-built mechanism of sustenance and

conservation. However, due to anthropogenic pressure, demand of more food have

cleared greater chunks of forests, fallow phase between two successive cropping

phases has come down to even 2 to 3 years ( Xu et al., 2009). This is adversely

affecting eco-restoration and ecological process of forests (Kiyoshi, 1999). Shorter

fallow periods are often allowing dominance of herbaceous weeds and soil erosion.

As a result, yields are being adversely affected and gradually declining over a period

of time.

29

Among many factors responsible for lower crop yield here, few are

prevalence of jhum cultivation, hilly terrain, unpredictable climate changes, low

levels of modern input use, poor infrastructure etc. Moreover, anthropological, socio-

cultural and economical characteristics of local farmers are also of hindrance for blind

adoption of tools/technology copied or transplanted from other geographical region.

With this background, in present review an attempt has been made to highlight socio-

economic changes due to transition from traditional to settled cultivation in NERI and

finds out root causes of low agricultural productivity of this region. Effort has also

been made to demonstrate existing scenario of ergonomic interventions in agriculture

of NERI and to draw future directions to come up with better ergonomic design

strategies for improvement of agricultural hand-tools and machines for making NERI

as self-dependent food grain producer (Patel et al., 2013).

Pace of mechanization in NERI has seen a relatively slow progress

over the years due to hilly topography, socio-economic conditions, small land

holding, lack of farm machinery manufacturing industries etc. Failure for adoption of

technology may be due to fragmental land, as 80% farmers belong to small and

marginal category (Deb and Ray 2006). Jhum cultivation is characterized as “cafeteria

system of cultivation”, where almost all the varieties of cereals and vegetables,

together with tree crops, are grown in a single field. Development of agriculture and

production of food grains in NERI is highly depending upon the custom, culture and

food habit of the tribal people (Patel et al., 2013).

In Mizoram, majority of population (~60%) are dependent on

agriculture production for their livelihood, however, only 5% of the total area is under

cultivation and about 7% of the total cultivated area is under irrigation (Anon., 2010).

30

Maize and paddy are the major food crops cultivated on the hill slopes and rely on the

natural rainfall which is triggered by the south-west monsoon. In addition, pulses,

sugarcanes, chillies, ginger, tobacco, vegetables, turmeric, potato, bananas and

pineapples are the crops grown in the state. Forest accounts for nearly 89% of the total

land area. State has undulating terrain which is divided into hills and valleys. Hills run

north to south direction parallel to each other with valleys in between the two hills.

Hills can be broadly categorized as: (i) high hills (> 1300 m amsl), (ii) medium hills

(between 500 m and 1300 m amsl) and (iii) low hills (< 500 m amsl). According to

land classification of the state based on soil survey, 58,638 ha of land has been

demarcated as available potential land for paddy and other seasonal crops cultivation.

The moderate slopes falling under Class III (55,196 ha), Class IV (1,50,015 ha) and

Class VI (10,12,114 ha) which are suitable for terracing, horticulture and plantation

crops respectively. (Lalnunmawia and Tripathi, 2015).

At least 70% of the state’s total planimetric land area (~2,108700 ha) is

sloped at angles steeper than 33 (Anonymous 2009c). Approximately half of all

households in Mizoram are engaged in jhum cultivation (Anonymous 2009c),

primarily in relatively undeveloped remote villages (Singh et al., 2010). Remote-

sensing based estimates of the total area burned each year by farmers and wildfires

range from 40,000 to 110,000 ha (Anonymous 2009b&c; Singh and Savant, 2000;

Tawnenga et al., 1996). The problems of declining soil fertility, lowered crop

productivity, and increased soil erosional losses with shortened fallow periods may be

even greater than on gently sloped regions (Fujisaka 1991; Roder et al., 1997;

Turkelboom et al., 2008).

31

The stability and future of many soils is under threat from a wide

variety of human activities including over-grazing, poor agricultural practices, land-

use change and forest clearance (Chris Park, 2001). Jhum cycles have been drastically

narrowed down and due to the loss of soil nutrients, productivity of crop yield

decreases (Sharma, 1984). With the increase land use, the cycle of cultivation is

affected and it has been observed that, Jhum cycle has been reduced from 10-15 years

now to 8-10 years. In some ranges in the district it has come down to 2-5 years. Due

to the reduction in cycle, the resilience of ecosystems has been broken down and the

land falls into deteriorating condition. Under this, the land is deteriorated with more

vulnerable to soil erosion and loss of soil fertility.

1.8 GENERAL DESCRIPTION OF MAIZE

Maize (Zea mays L) is the world’s most widely grown cereal and it is

ranked third among major cereal crops following Rice and Wheat (Ayisi & Poswall,

1997). It is cultivated as a single crop or in mixed cropping. It is a versatile crop and

is grown extensively with equal success in temperate, sub-tropical and tropical

regions of the world. Maize crop is a key source of food and livelihood for millions of

people in many countries of the world (FAO, 2002).

Maize is an annual short days, tall, determinate, C4 plant varying in

height from 1 to 4m producing large, narrow, opposing leaves, borne alternately along

the length of a solid stem. Maize plant have an erect stem which bear alternate leaves

tassel at the top and auxiliary female inflorescence known as ear in the middle (Azam

et al., 2007). All maize varieties follow same general pattern of development,

32

although specific time and interval between stages and total number of leaves

developed may vary between different hybrids, seasons, time of planting and location.

Maize is a monoecious plant. It has determinate growth habit and the

shoot terminates into the inflorescences bearing staminate (tassel) or pistillate (ear)

flowers (Dhillon and Prasanna, 2001). Maize is generally protandrous, that is, the

male flower matures earlier than the female flower. Within each male flower spikelet,

there are usually two functional florets. Each floret contains a pair of thin scales i.e.

lemma and palea, three anthers, two lodicules and rudimentary pistil. Pollen grains

per anther have been reported to range from 2000 to 7500. The pollen grains are very

small, barely visible to the naked eye, light in weight, and easily carried by wind. The

wind borne nature of the pollen and protandry lead to cross-pollination, but there may

be about 5 per cent self-pollination (Kiesselbach, 1949).

The female inflorescence or ear develops from one or more lateral

branches (shanks) usually borne about half-way up the main stalk from auxillary

shoot buds.. As the internodes of the shanks are condensed, the ear remains

permanently enclosed in a mantle of many husk leaves. Thus the plant is unable to

disperse its seeds in the manner of a wild plant and instead it depends upon human

intervention for seed shelling and propagation (Kiesselbach, 1949).

1.8.1 Taxonomy of maize

Maize (Zea mays L.) belongs to the family Poaceae (Gramineae) and

the tribe Maydeae. The genus Zea consists of four species of which Zea mays L. is

economically important. The other Zea sp., referred to as teosintes, are largely wild

33

grasses native to Mexico and Central America (Doeblay, 1990). The number of

chromosomes in Zea mays is 2 n = 20.

Tribe Maydeae comprises seven genera which are recognized, namely

Old and New World groups. Old World comprises Coix (2n = 10/20), Chionachne (2n

= 20), Sclerachne (2n = 20), Trilobachne (2n = 20) and Polytoca (2n = 20), and New

World group has Zea and Tripsacum. It is generally agreed that maize phylogeny was

largely determined by the American genera Zea and Tripsacum, however it is

accepted that the genus Coix contributed to the phylogenetic development of the

species Zea mays (Radu et al., 1997).

Systematic Position:

Kingdom ----- Plantae

Division ----- Magnoliophyta

Class ----- Liliopsida

Order ----- Poales

Family ----- Poaceae

Genus ----- Zea

Species ----- Z. mays

1.8.2 History of maize cultivation

The center of origin for Zea mays has been established as the

Mesoamerican region, now Mexico and Central America. Archaeological records

suggest that domestication of maize began at least 6000 years ago, occurring

independently in regions of the southwestern United States, Mexico, and Central

34

America (Watson and Dallwitz, 1992). The Portuguese introduced maize to

Southeast-Asia from the America in the 16th century. The maize was introduced into

Spain after the return of Columbus from America and from Spain it went to France,

Italy and Turkey. In India, Portuguese introduced maize during the seventeenth

century. From India it went to China and later it was introduced in Philippines and the

East Indies. Maize now is being grown in USA, China, Brazil, Argentina, Mexico,

South Africa, Rumania, Yugoslavia and India. In respect of production USA stands

first (Mangelsdorf, 1974).

Various hypothesis have been proposed on the origin/domestication of

maize (OECD, 2006). Teosintes (Z. diploperennis and Z. mays sp. mexicana) and

Tripsacum species are often described as having roles in the domestication process of

maize (Mangelsdorf, 1974; Galinat, 1988). An early hypothesis proposed that Z. mays

sp. mexicana was the product of a natural hybridization of Tripsacum and Zea

(Mangelsdorf, 1974). Further crossings of teosinte with wild maize are thought to

have produced the modern races of maize. The possibility of intergeneric

hybridization of either Z. diploperennis or Tripsacum with an extinct wild maize has

also been proposed as the ancestral origin of Z. mays (Radu et al., 1997; Purseglove,

1972). Eubanks (1993, 1997a) suggests that domesticated maize may have arisen via

human selection of natural hybrids between Tripsacum and perennial teosinte.

1.8.3 Germplasm diversity

Maize is a cultivated crop throughout the world and accordingly

germplasm resources are preserved ex situ in many parts of the world. Most of the

maize variation can be found in the Meso-American region and the northern part of

South America. The great diversity of environments and conditions have created the

35

basis for the development of maize varieties well adapted to harsh conditions of soil

and climate as well as to biotic stresses. There is a close correlation among

community culture, production system and the type of consumption of maize, with the

diversification and variation of maize (Aguirre et al., 1998; Louette and Smale, 1998).

There is a growing trend in developing countries to adopt improved maize varieties.

In Mexico, only 20% of the corn varieties grown 50 years ago remain in cultivation

(World Watch Institute, 2000). CIMMYT (International Maize and Wheat

Improvement Centre) has taken the lead in preserving maize germplasm. It has the

world’s largest collection of maize accessions, with over 17,000 lines (CIMMYT,

2000).

India also harbours diverse maize germplasm (Singh, 1977; Wilkes,

1981). An extensive collection of germplasm from the entire NEH region has been

made by the Indian Agricultural Research Institute, New Delhi. It has been shown

that the two primitive Sikkim maize strains (Sikkim Primitive 1 and Sikkim Primitive

2) were different from the primitive Mexican races (Mukherjee et al., 1971). Indian

maize races have been classified under four categories i.e. primitive group, advanced

or derived group, recent introduction and hybrid races (Singh, 1977). The National

Gene Bank at New Delhi houses about 6,000 indigenous accessions primarily from

the NEH region. Systematic and comprehensive evaluation of this germplasm is

being attempted for agronomically useful traits (Prasanna et al, 2009). In addition to

the races, there are several local varieties in India. The genetic variability has resulted

by crossing of Indian germplasm with strains imported from other countries

particularly USA (Mukherjee, 1989). It has been reported that crosses of Indian x

Indian germplasm gave yield superiority of 24-43 per cent, whereas Indian x US dent

germplasm out yielded local varieties by 58 per cent (Dhawan and Singh, 1961).

36

Highest yielding single cross hybrids were obtained from crosses between Indian x

USA germplasm followed by USA x USA and Indian x Indian germplasm, thus

highlighting the significance of genetic divergence for obtaining higher yields

(Ahloowalia and Dhawan, 1963). Dent x flint crosses involving Indian and

Caribbean, and Indian and US germplasm showed highest expression of heterosis

over better parent (47-54%) (Mukherjee and Dhawan, 1970).

1.8.4 Conditions for maize cultivation

Maize crop is primarily a warm weather crop and it is grown in wide

range of climatic conditions and it is more extensively distributed over the earth than

any other local crops Maize is a kharif crop and is grown as a summer annual. Maize

cultivation consists of sowing, harvesting, threshing (ICAR, 2006). It is widely

cultivated from the sea level up to altitudes of 2,500m. Maize grow best under Sub-

tropical condition. The temperature requirements of the growing plant ranges from

210C to 280C. The plant requires about 140 days of bright warm sunshine and about

60-120cm of average rainfall, to attain full maturity. An alkaline, well-drained loamy

soil produces the best results. It can’t withstand frost at any stages of its growth

(Onwueme and Sinha, 1991).

Maize require fertile, deep and well-drained soil. However, it can be

grown on any type of soil, ranging from deep heavy clays to light sandy ones. It is

necessary that, the pH of the soil does not deviated from the range of 7.5 to 8.5. Maize

crop requires about 50% of its total water requirement in a short period of 30-35 days

after tasselling. The productivity of maize largely depends on its nutrient requirement

37

and management particularly that of nitrogen, phosphorus and potassium (Arun et al.,

2007).

Maize has a high grain yield potential, which is determined by the

genetics of the cultivated hybrid and is influenced by the environmental factors that

are affecting the plant growth. In order to fully explore their capacity to transform

solar radiation into grain production, it is necessary to understand how plants interact

morphologically and physiologically in a community and to identify the management

practices which allow them to maximize the use of growth resources (Sangoi, 2001).

Maize yields variations between regions or agro-ecological zones can

be attributed to various factors of which some are agronomic like plant density,

planting dates, and soil fertility (Banziger et al., 2000). Successful maize production

requires an understanding of various management practices as well as environmental

conditions that affect crop performance (Eckert, 1995).

1.8.5 Economic importance of maize

Maize is an important food crop grown commercially in large scale

and at subsistence level by many resource poor farmers. It is known as queen of

cereals because it has the highest genetic yield potential among the cereals. It matures

earlier than most food crops and it is used in homes to prepare different dishes

especially during the “hungry period” of June - July when most other crops had been

planted by the farmers (Onwueme and Sinha, 1991).

` Maize has great significance as human food, animal feed and raw

material. In most developing countries, about 50 to 55 percent of the total maize

production is consumed as food. Maize has high production potential especially under

38

irrigated condition when compared to any other cereal crop. The maize grain can be

prepared for food in many different ways (fried, grilled, in a salad or soup).

Processing maize can also produce a wide range of products such as corn flour and

corn meal. Maize is also used in livestock feed (poultry, pigs, cattle) in the form of

grains, feed milling or as fodder (Morris, 1998).

The use of maize varies in different countries. In USA, European

countries, Canada and other developed countries, maize is used mainly to feed

animals directly or sold to feed industry and as raw materials for industrial products

such as starch, glucose, dextrose (FAO, 1999), starch and specialized foods. Starch in

turn involves in the enzymatic conversion into products such as sorbitol, dextrine,

sorbic and lactic acid, and appears in household items such as beer, ice cream, syrup,

shoe polish, glue, fireworks, ink, batteries, mustard, cosmetics, aspirin and paint. It is

also being recently used as biofuel (Galinat, 1988; Shaw, 1988, Mexico, 1994). Most

people regard maize as a breakfast cereal. In Latin America and Africa the main use

of maize is for food while in Asia it is used for food and animal feed. In fact in many

countries it is the basic staple food and an important ingredient in the diets of people.

Globally, it has been estimated that approximately 21% of the total grain produced is

consumed as food (Shaw, 1988).

In India, about 28% of maize produced is used for food purpose, about

11% as livestock feed, 48% as poultry feed, 12% in wet milling industry (for example

starch and oil production) and 1% as seed (AICRP on Maize, 2007). The increase in

consumption of maize is also due to the renewed interest in traditional dishes and

diversified maize production, that can be used for livestock feed or industrial energy,

because it is adapted to a wide range of environmental conditions (Malvar et al.,

39

2008). Maize is a crop par excellence for food, feed and industrial utilization.

(Gopalan et al., 2007).

Table 1.1: Composition per 100 g of edible portion of maize (dry)

However, it is deficit in essential amino acid, lysine and tryptophan. To overcome this

deficiency, quality protein maize (QPM) with sufficiently higher quantity of lysine

and tryptophan have been developed.

1.8.6 Maize production

Maize is cultivated on nearly 178 million ha globally in about 160

countries and contributes ~50% (1,170 million MT) to the global grain production.

The major maize production areas are located in temperate regions of the globe. The

Moisture 14.9 g Minerals 1.5 g

Protein 11.1g Carbohydrates 66.2 g

Fat 3.6 g Calcium 10 mg

Fibre 2.7 g Iron 2.3 mg

Calories 342 Potassium 286 mg

Phosphorus 348 mg Thiamine 0.42 mg

Sodium 15.9 mg Carotene 90 ug

Sulphur 114 mg Vitamin C 0.12 mg

Riboflavin 0.10 mg Magnesium 139 mg

Amino acids 1.78 mg Copper 0.14 mg

40

United States, China, Brazil and Mexico account for 70% of global production. India

has 5% of corn acreage and contributes 2% of world production (FAOSTAT, 2014).

Table 1.2. Top ten maize producers in 2013 (FAOSTAT 2014)

Animal feed is the largest end use segment for maize in Asia with

~70% of total volumes used by feed industry. It is estimated that the demand for

maize will be fueled by population growth and increasing inclination towards higher

protein consumption in the form of meat and eggs. Maize, as poultry feed, is more

acceptable than rice and wheat both in terms of price and nutrition. The nutritional

value of maize is higher (3,365 Kcal/kg) compared to rice (3,320 Kcal/kg), rice bran

Country Production (tonnes)

United States 353,699,441

China 217,730,000

Brazil 80,516,571

Argentina 32,119,211

Ukraine 30,949,550

India 23,290,000

Mexico 22,663,953

Indonesia 18,511,853

France 15,053,100

South Africa 12,365,000

World 1,016,431,783

41

(2,620 Kcal/kg), peanut (2,915 Kcal/kg) and oilcake (2,350Kcal/kg). Apart from feed

and industrial applications, food processing industry is a crucial end use segment for

maize as it is being used for making food additives and sweeteners. With processed

food industry slated to grow at 10%+ rate in the next five years in most countries of

South East Asia maize demand is expected to rise. As per the OECD agricultural

outlook report, biofuel volumes for southeast Asia are expected to grow from 4.9

billion liters in 2013 to 7.5 billion liters by 2021 at an annual growth rate of 5.5%

backed by favorable policies in SE Asian countries (FAOSTAT 2014).

In India, maize constitutes about 9% of the total volume of cereals

produced and is the third most important food grain after rice (~42%) and wheat

(~38%). Advance estimates for total production in India stands at 9.3 million MT in

trade year 2015, growing at about 6% in the past 5 years (Farnharm et al., 2003).

Maize has diverse industrial applications with its primary usage being in feed. Poultry

industry is heavily dependent on maize as it forms 50-60% of the input required for

broiler feed and 25-35% of the input required for layer feed. Broilers consume 3.6-4

kgs of feed over a period of 32 - 35 days ( 5 weeks) to attain weight of ~2.2 kg.

Layers have a life span of ~72 weeks of which they lay eggs for 52 weeks with an

annual feed consumption of 42 - 47 kgs, producing over 300 eggs. The industry

standard for energy requirement is 3,200 Kcal/ kg in case of broiler feed and 2,300

Kcal/ kg in case of layer feed. Maize provides approximately 3,400 kcal/ kg and is

most preferred due to availability and higher energy content. Jowar is the closest

substitute but its availability is constrained while wheat contains high non-starch

polysaccharides which are indigestible by broilers and have to be depolymerized with

an enzyme for release of energy. Better quality maize can be developed for this

42

industry with higher energy content in order to ensure there is no substitution (ICAR,

2006).

1.8.7 Maize cultivation and production in Mizoram

In Mizoram more than 90 percent of the area comes under hills

(Vishwakarma et al., 2012). Agriculture occupies a very important place in the

economy of Mizoram. As per Economic Classification of workers 2001 census, about

60% percent of the total workers are engaged in Agricultural and allied sector. The

economic life of the Mizo has always been centered around jhum or shifting

cultivation (Economic Survey Mizoram 2013-14).

Maize is the second most important crops next to paddy in jhum areas

and is generally sown with the onset of monsoon as kharif crop. However, increasing

trends in production for Rabi maize is also observed with the introduction of new high

yielding varieties associated with irrigation facilities. In term of area and production

in Mizoram, maize occupy 10810 ha (Kharif) and 932 ha (rabi) respectively.

(Anonymous, 2007). The other common crops in Mizoram are cucumber, beans,

ginger, mustard, sesame, cotton etc. It is also practiced by the Mizo farmers to grow

multiple crops together with maize. Some of the most common crops mixed with

maize are brinjal, chilli, sesame, mustard, peas, pumpkin and white pumpkin. In

Mizoram, Maize is graded in two varieties viz. big maize (Locally named Mimpui)

and sticky maize (Locally named Mimban).

The total area under maize cultivation is also increased from 8000 ha.

during 2012-13 against 6905 ha during 2011-12 which account for 15.85 % increased

in area and 25.04 % increased in production over the preceding years (Economic

43

Survey Mizoram 2013-14). Maize is not only important for humans but also being

consumed as feed materials for poultry and pigs. The productivity of maize is low

(1621 kg/ha) as compared to the national productivity of 2000 kg/ ha (Vishwakarma

et al., 2012).

In the early period of agriculture in Mizoram, sufficient land was

available to meet the demand for agricultural land of the low density population. After

cultivation, the land was left fallow for about 25 years or even more which

synchronized well with the time required for the maturity of the forest and recovery of

the fertility of the soil. However, with the increase in population, the pressure on land

has increased and consequently, the fallow periods have been reduced significantly

leading to the transformation of once a fertile land into unsustainable marginal land

(Tawnenga et al., 1996).

Maize cultivation in the jhum and valley with little or without chemical

and organic fertilizers is a limiting factor of increasing productivity in Mizoram. The

farmers used locally available low cost manure as sole nutrition to the rainfed maize

crop grown mainly in jhum, valley or home yard land. Moreover, due to the

introduction of “The Mizoram organic Bill 2004” on 12th July 2004, organic farming

plays a very significant role as far as production of crops is concerned for the whole

state of Mizoram (Economic Survey Mizoram, 2013-14). Farmers are therefore

encourage to adopt the utilization and package of practices of various green manuring

crops and bio-fertilizers so as to boast the production and also to improve the soil

fertility status in the long run the best time of growing, and number of population in

an area by providing them research base data and figures.

44

1.9 Scope of the study

Despite of the long history of maize cultivation, standardization and

optimization of its production with reference to cultural practice is lacking in

Mizoram. The total production of maize is not sufficient to meet the requirement of

maize for the population of Mizoram (Anon., 2006). The cultivation of maize with

proper management of soil fertility status by application of different doses of NPK

fertilizers and plant population/spacing on an input requirement may be the only

possible solution to increase the productivity of maize in Mizoram on sustainable

basis. Besides there is an increasing population in the state due to which jhum

cultivation with short duration cycles is now being considered as an economic as well

as environment liability.

However, research findings on maize cultivation, its nutritional

requirements and the influence of fertilizers and plant spacing on growth and yield

attributes of the local maize variety (Mimpui) are very scarce. The present study

therefore, aims to investigate the growth and productivity of maize with different

fertilizer doses and different plant population density in different fallow periods of

Mizoram. It is expected that the present study would help in suggesting the most

suitable plant spacing and appropriate soil and nutrient management to increase the

productivity of maize in different jhum cycles.

45

1.10 Objectives

The present study aims to understand the comparative analysis of

growth and productivity of maize in different jhum cycles of Mizoram. Thus, the

specific objectives of the present study are as follows:

1. To study the effect of different fertility levels on growth and yield of

maize under different jhum cycles.

2. To find out the suitable spacing for growth and yield of maize.

46

Chapter – II

REVIEW OF LITERATURE

2.1 Jhum cycles and sustainable agriculture

The length of the cultivation period varies depending on the region

(one to three years), but is always shorter than the fallow period. The fallow period

may be natural or managed and allows recovery from the soil degradation resulting

from conversion and cultivation. The duration of the fallow period is variable, but it

must be long enough for woody vegetation to become dominant (Eden and Andrade,

1987; Kleinman et al., 1995; Mertz et al., 2009). The jhum cultivation leads to the

formation of mosaics of secondary forests in different stages of regeneration,

contained within a mature forest matrix that helps to sustain them (Conklin, 1961;

Harris, 1971; Hiraoka and Yamamoto, 1980; Egger, 1981; Altieri et al., 1987;

McGrath, 1987; Adams, 2000a; Martins, 2005).

Jhum cultivation appears to be sustainable under specific conditions of

low demographic densities and the use of low input technologies (Kleinman et al.,

1995; Johnson et al., 2001; Pedroso junior, 2008, 2009). However, the rapid and

important climatic and economic-political transformations that have occurred in

recent decades (Mertz, 2002; Pedroso-Junior et al., 2008, 2009; Van Vliet et al.,

2012) have produced a growing concern about the sustainability of SCS (Bruun et al.,

2009) and the food security of subsistence farmers (Altieri et al., 1987; Adams et al.,

2005).

During the 1950s, the Food and Agriculture Organization of the United

Nations (FAO, 1957) requested that governments, research centers, and public and

47

private associations invested in the modernization of agricultural practices and

disregarded those associated with shifting cultivation. According to FAO, shifting

cultivation represented a backward and inadequate system for the conservation of the

tropical forest ecosystems in which it was practiced (Mertz et al., 2009). The practice

of Jhum is not, merely exercised by the tribals for their sustenance, but a traditional

method of earning a livelihood, a traditional farming system that uses local product

and techniques, has rooted in the past, has evolved to their present stage as a result of

the interaction of the cultural and environmental condition of the region and is deeply

embedded in the tribal psyche (Gupta, 2005).

Chhauchhuak (2004) reported that crop mix of perennial and season

crops in Jhum cultivation allows phased harvesting ensuring food security throughout

the year and also provide needed diversity for nutrition and food preferences. Sarangi

& Singh (2007) observed that pseudo cereals, small millets, indigenous pulses, oil

seeds and many forest plants form an important component of food source for the

tribal population. Species have been used as life sustaining food as well as medicines

from time immemorial.

The availability of Non Timber Forest Products serves as an important

gap-filler when food stocks are low and also as a source of income. For example, the

collection of indigenous fruits contributes between 5.5 and 6.5% to the total

household income in the rural communities of Southern Africa (Akinnifesi et al.,

2008). The tribal people of the Chittagong Hill Tract of Bangladesh still practice jhum

as a principal source of livelihood. But a rapid rise in population (both endemic and

migration influx of plains people), the construction of development infrastructure (e.g.

hydroelectric projects), and government policies on expansion of reserve and

48

protected forests has made the jhum vulnerable (Nath et al., 2005). Belsky & Siebert

(2003) stated that farmers in the Chittagong Hill Tract who live mostly in inaccessible

hilly areas and are deprived of all humanitarian services and facilities are forced to

practice traditional jhum. In order to maintain their livelihoods, there is need to

balance food and income generation, and a combination of on- and off-farm

enterprises helps to maintain the balance.

Forest income arises more from non-timber forest products (NTFPs)

and forest ecosystems services than from timber. The mere existence of forest

resources and related cultural heritages is not enough for local communities to obtain

income from forest land. Proper arrangements for local communities in accessing the

forest resources and knowledge of making use of the resources is required to make the

relationship constructive for people’s livelihood in South Korea (Yeo-Chang 2009).

Mertz (2002) stated that although introduced changes may indeed be very valuable for

local livelihoods and environment, there is little evidence that shifting cultivation will

ever reach a stage of environmental degradation and low productivity, which could be

considered a "breakdown" of the system.

Toky and Ramakrishnan, (1981) compared the structure and functional

aspects of three agro-ecosystem types i.e, jhum cultivation, valley rice cultivation and

terrace cultivation and reported that the 30 year jhum cycle has the advantage over the

10 or 5 year cycle apart from higher yields, in that the monetary output/input ratio

under a 30 year jhum cycle is comparatively favourable.

Lele et al., (2008) studied six historical data sets of Northeastern

region (NER) of India, one of the largest reserves of forests in India, generated from

remote sensing data (1972, 1982, 1987, 1989, 1993 and 1999) and are used to assess

49

forest cover loss, shape index and entropy to the degree of forest fragmentation over a

multi-decadal period. The assessments have been carried out in the open (40–10%

canopy density) and close (>40% canopy density) forest cover classes. The range of

shape index and deviation from the actual mean in open forest and closed forest were

computed separately. The patches among two categories were further analyzed based

on patch area into six classes; ranging from <1 km2 to >500 km2. This also indicates

variability of the forest patches. It is noteworthy that patches of area within 1–

10 km2 and 10–50 km2 have been severely fragmented. This loss could be attributed

to the shifting cultivation practice where the patches of moderate size are cultivated

by group of families.

The practice of jhum is not merely another exercise by the tribals for

their subsistence, but a traditional method of earning a livelihood, a traditional

farming system that uses local products and techniques, has roots in the past, has

evolved to their present stage as a result of the interaction of the cultural and

environmental conditions of the region and is deeply embedded in the tribal people

(Katherine, 1991).

The influence of fallow period on economic yields and soil

biogeochemistry were studied by comparing replicate fields of similar slope that were

under 5, 10 and 30 year fallow rotation periods. Mean annual total economic yields

over a full rotational cycle were twice as high in the 10 and 30 year compared to the 5

year fallow systems (Toky and Ramakrishnan 1981a). Mean annual losses of major

soluble nutrients in run-off (plus downward percolating waters) did not differ between

fields of varying fallow period, but surface run-off sediment losses were ~40% higher

in the shortest fallow fields (Toky and Ramakrishnan 1981b).

50

Cultivation on burned sites could be extended by effective cropping in

the second year after burning was tested in two sites under differing fallow periods in

Mizoram (Tawnenga et al., 1996). Ecosystem productivity (total dry matter

production in crops and weeds) in a 6 year fallow site during the two successive years

after burning was 45 and 22% lower, respectively, than in a 20 year fallow site. Soil

organic carbon, total nitrogen, extractable phosphorus and exchangable cation pools

were all depleted in the shorter fallow site, and soluble nutrients progressively

declined during each of the successive cropping years at both sites (Tawnenga et al.,

1997b). Commercial fertilizer and/or farmyard manure additions in the second year

elevated productivity in the short and long fallow period sites by ~50 and ~33%,

respectively.

2.2 Effect of Fertilizers on Maize

Integrated use of balanced inorganic fertilizer in combination with

lime and organic manure sustains a better soil health for achieving higher crop

productivity under intensive cropping systems in hilly ecosystem of north eastern

India. Study suggests that addition of NPK fertilizers along with organic manure,

lime, and biofertilizers had increased SOC content, aggregate stability, moisture

retention capacity, and infiltration rate of the soil while reducing bulk density. The

SOC content under the treatment 100% NPK + lime + biofertilizer + FYM was

significantly higher (68.6%) than control plots (Saha et al., 2010).

It was reported that the low fertility status of most tropical soils

hindered maize production as maize has a strong exhausting effect on the soil. It was

generally observed that maize fails to produce good grain in plots without adequate

nutrients (Adediran and Banjoko, 2003). Inorganic fertilizer exert strong influence on

51

plant growth, development and yield (Stefano et al., 2004).The availability of

sufficient growth nutrients from inorganic fertilizers lead to improved cell activities,

enhanced cellk multiplication and enlargement and luxuriant growth (Fashina et al.,

2002). Luxuriant growth resulting from fertilizer application leads to larger dry matter

production (Obi et al., 2005) owing better utilization of solar radiation and more

nutrient (Saeed et al., 2001).

Yield differences between temperate and tropical areas have been

attributed to low nutrient status of tropical soils especially nitrogen, phosphorus and

potassium resulting from the practice of slash and burn farming system associated

with bush fallow and with excessive leaching of the soil nutrients. This system is

presently unsustainable due to high population pressure and other human activities

which have resulted in reduced fallow period (Steiner, 1991).

Acid soils are highly weathered and contain large quantities of Al and

Fe hydrous oxides that have the ability to absorb major elements onto their surfaces

such that much of added nutrients are fixed instead of being made available for crop

use ( Enwezor et al., 1981; Akinrinade et al., 2006). Vast areas of tropical lands that

were once fertile have been rendered unproductive due to continuous cultivation and

erosion which caused physical degradation, loss of soils organic matter and decreased

cation exchange capacity (CEC) and as well as increased Al and Mn toxicity (Mba,

2006). As these soils suffered multi-nutrient deficiencies, application of mineral

fertilizers has become mandatory to increase crop yields. However, mineral fertilizers

are commonly scarce, costly, having imbalanced nutrition and their use could

exacerbate the problem of soil acidity (Oguike et al., 2006; Nottidge et al., 2006).

52

Nitrogen is a primary nutrient required by crop plants for their growth

and development. Nitrogen plays a key role in vegetative growth and grain production

of maize plant (Adediran and Banjoko,1995; Shanti et al., 1997). The application of

nitrogen not only affects the forage yield of maize, but also improves its quality

especially its protein contents (Haque et al., 2001). It is reported that application of

nitrogen to maize increase fodder nutritive value by increasing crude protein and by

reducing ash and fiber contents (Baran, 1987). Plant height, stem diameter, green

fodder yield, protein, fiber, and total ash content were increased by increasing

nitrogen levels. It also mediates the utilization of phosphorus, potassium and other

elements in plants (Brady, 1984).

Phosphorus is considered an essential nutrient to plant growth and

development. It is an integral part of nucleic acid and is essential for cellular

respiration and for metabolic activity. Therefore, the use of phosphorus along with

nitrogen will help increase yield of maize (Safdar, 1997). Phosphorus application

increased fodder yield and quality by increasing plant height, and the number of

leaves plant1 (Masood et al., 2011).

Potassium is a multifunctional and high mobility element with direct

and in direct influence on almost all biochemical and biophysiological processes. It

catalyzes numerous enzyme reactions. It helps the formation, transport and deposit of

the products of photosynthesis in fruits, grains, tubercles and contributes to their

transformation in fibers proteins, fats and vitamins (Adediran and Banjoko,1995).

Potassium increases root growth and improves drought resistance; maintains turgor;

reduces water loss and wilting reduces respiration, preventing energy losses; enhance

strains location of sugars and starch; produces grain rich in starch, increases protein

53

content of plants, builds cellulose and reduces lodging, helps retard crop diseases.

Potassium plays significant roles in enhancing crop quality (Rehm et al.,1983).

The nitrate N is easily lost through leaching and denitrification in field

soil, whereas the ammonium N is usually lost through volatilization (Janzen et al.,

2013; Li et al., 2014). Many approaches have been practiced for improving N

utilization efficiency in crops, for example, optimal time, rate, and methods of

application for matching N supply with crop demand and the use of specially

formulated forms of fertilizer. The results showed that N application by stages can

significantly increase maize grain yield compared to disposable application as sowing

manure (Yu et al., 2010). Zhang et al., (2014) reported that the regulating N

application (240 kg/ha, divide into 3 equal amounts, each about 80 kg, used as base

fertilizer, tillering fertilizer, and booting fertilizer) could increase rice yield while

substantially reduced N leaching losses and improved N use efficiency.

Nitrogen has a major effect on growth among the major nutrients

needed by plants (especially the three elements of N, P, K) (Costa et al., 2002., Kagbe

and Aderian, 2003) and Plants give it different responses. Maize need to nitrogen is

different due to weather conditions, soil type and maize rotation (Bundy, et al., 1993.,

Green and Blackmer, 1995).

Soil nutrition absorbed by crops can be divided into mobile and

immobile (Barber, 1995). Nitrogen (N) in form of nitrate and water are highly mobile

and required in largest amounts by crops. Phosphorus (P) is the most immobile, and

potassium (K) is also relatively immobile, both of which are macronutrients required

by crops (Marschner, 2012). The contents of N, P and K in agricultural soil are

affected by plant growth and yield (Havlin et al., 2004). Therefore, crop yield is

54

limited by two important mobile resources, including nitrate and water, as well as two

immobile resources, P and K (Lynch, 2013).

Khan et al., (2014) investigated the response of maize to three

phosphorus rates (60, 90 and 120 kg∙ha−1) and four nitrogen rates (90, 120, 150, 180

kg∙ha−1) for number of plant per m2 (NP m2), plant height (PH), number of leaves

plant−1 (NLP), fresh weight of plants kg∙ha−1 (FW) and dry weight of plant kg∙ha−1.

Results of the study showed that application of N @ 180 and P @ 120 kg∙ha−1

significantly increased fodder yield of maize. The linear increase in biomass yield

clearly indicated that N was a limiting nutrient factor and that N demand along with P

has a positive response. At higher application rates, N fertilizer significantly increased

biomass component, improved N uptake with increasing nitrogen use efficiency and

decreased its losses to the environment and below plant zone.

A two years field study was conducted to examine the agronomic

response, efficiency and profitability of fertilizer microdosing in maize with the rate

of 27 + 27, 53 + 53 and 80 + 80 kg ha−1, and banding of fertilizer with 100 + 100 kg

ha−1 of di ammonium phosphate (DAP) + urea, applied at planting and jointing,

respectively. The 27 + 27 kg ha−1 fertilizer rate increased the grain yield by 19, 45

and 46% and it was equivalent to the higher rates. The value cost ratio (VCR) was

highest with the lowest fertilizer rate, varying between seven and 11 in the treatment

with 27 + 27 kg ha−1. The improved yield, Fertilizer Use efficiency (FUE), Value

Cost Ratio (VCR) and gross margin in maize with microdosing at the 27 + 27 kg ha−1

of DAP + urea rate makes it low cost, low risk, high yielding and profitable. (Sime

and Aune, 2014).

55

Xian et al., (2014) conducted an experiment to study the effects of

different N application rates on the yield and nitrogen utilization efficiency of summer

maize and reported that the yield increased at first and then decreased with the

increase of N application rates. With the increase of N application rate harvest index

(HI) and N harvest index (NHI) decreased. The highest HI and NHI was obtained at N

application of 189 kg/ha (N189) and 178 kg/ha (N178). Excessive N application rate

reduced N recovery efficiency (NRE) and N partial fertilizer productivity (NPFP) by

29%-55% and 32-64 kg/kg compared with N189 and N178, respectively. Agronomic

efficiency(AE) and physiological efficiency(PE) increased at first then decreased with

the increase N application rate, and the highest AE and PE were appeared at N

application rate of 200 kg/ha.

It was reported that the grain yield of maize increases first, and then

decreases with the increase of nitrogen application rates, and reaches the highest at

150-180 kg N/ha, appropriate nitrogen rate could improve grain equality, N use

efficiency and N partial factor productivity decline as N application increased,

respectively. (Hu et al., 2014).

Nitrogen element is the nutrient that most frequently limits yield and

plays an important role in quality of forage crops (Jules, 1974). Positive response of

nitrogen fertilizers has been reported by Koul, (1997). Nitrogen fertilization increased

number of leaves per plant and leaf area (El Noeman et al., 1990 and Gasim,

2001). John and Warren (1967) noted that the addition of nitrogen increased stem

diameter. Koul (1997) recorded that nitrogen application resulted in greater values of

plant height, leaf area, number of leaves and stem diameter of fodder maize, fresh and

56

dry forage yield were also increased due to addition of nitrogen. Leaf to stem ratio

was found also to be increased by nitrogen (Duncan, 1980).

Gasim (2001) reported that the increase in leaf to stem ratio with

nitrogen application is probably due to the increase in number of leaves and leaf area

under nitrogen treatments, producing more and heavy leaves. The uptake of nitrogen

by maize is low during early development and increased at tasseling. Although only

relatively small amounts of fertilizers are required during the very early stages of

plant growth, high concentration of nutrients in the roots zone at that time are

beneficial in promoting early growth (Ritchie et al., 1993).

Sharma (1973) observed that addition of nitrogen fertilizer increased

plant height. Increase in plant height resulted in an increase in leaf number per plant

as reported by Akintoye, (1996). Gasim (2001) indicated that the increase in plant

height with nitrogen fertilizer is due to the fact that nitrogen promotes plant growth,

increases the number of internodes and length of the internodes which results in

progressive increase in plant height. Turkhede and Rajendra, (1978) and Koul,

(1997) reported similar results. Tripathi et al., (1979) found that application of

nitrogen gave a significant additional increase in crude protein contents of forage oats.

Kalifa et al., (1981) studied the effect of nitrogen on an open-

pollinated variety of corn which was given as ammonium nitrate applied as nitrogen

source. His results indicated that ammonium nitrate fertilizer increased the number of

days to mid- tasseling, mid-silking and shelling percentage. Singh et al., (1986) found

that the biological yield, content and uptake of nitrogen in grain and stover of maize

were highest with nitrogen as urea applied in two split dressings. Nitrogen had

significant effects on chemical composition of leaves, plant height, leaves, internodes

57

number per plant at early stages. Nitrogen also significantly affected final seed yield

and some yield components such as number and weight of cobs/m2and weight of

seeds per cob, also significantly affected straw yield. In addition nitrogen had

significant effect on seed protein content and seed and leaf P content (Omara, 1989).

High cost of inorganic fertilizers has precluded their use by

smallholder farmers to remedy the problem of soil acidity and infertility. Lime and P-

fertilizer significantly affected only the top-soil pH, Ca, Mg and available P, while the

effects of N-fertilizer were evident on both top- and sub-soil N likely due to its faster

mobility than P and lime (Kisinyo et al., 2015).

Phosphorus is one of the most important nutrients for sustainable crop

production in most acid soils of the tropics and subtropics (Ryan, 2002). Phosphorus

has a vital role in energy storage, root development and early maturity of crops. The P

requirement of crops is very high during initial stages of plant growth (Latif et al.,

1992). It has functions of a structural nature in macromolecules such as nucleic acids

and of energy transfer in metabolic path- ways of biosynthesis and degradation.

Unlike nitrate and sulphate, phosphate is not reduced in plants but remains in its

highest oxidized form (Marschner, 1993).

Enujeke (2013) recommended the application of 450kg ha-1 of NPK

20: 10:10 or 30 tha-1 of poultry manure for increased grain yield of maize. The report

further argued that poultry dropping and cattle dung increases root growth of maize

and the crop extracts soil water more efficiently for increased grain yield.

The values of N, P and K were higher in poultry manure than in cattle

dung because poultry manure, especially those produced in deep litter or battery cage

58

house, have more concentrated nutrient content compared with other types of animal

manure. This is similar to the findings of Sharpley and Smith (1995), Lombin et al.,

(1991). Low soil fertility of tropical soils, particularly low nitrogen, ranks the second

most important abiotic constraint to maize production in tropical ecologies (Pingalli,

2001). Intensified land use and the rapid decline in fallow periods, coupled with the

extension of agriculture into marginal lands, have contributed to a rapid decline in soil

fertility. Nitrogen (N) and phosphorus (P) deficits are a severe and widespread

biophysical constraint to smallholder maize productivity, and in turn to the long term

food security (Sanchez et al., 1997).

Ekesiobi et al., (2015) reported that the combined application of

organic and inorganic fertilizers significantly increased the plant height, number of

leaves, stem girth, leaf area and leaf area index and number of cobs, ear length, ear

diameter, weight of ear, weight of cob, 100 grain weight, grain yield t/ha and above

ground weight (yield parameters), particularly 10 t/ha poultry manure combined with

75 kg/ha urea, followed by 10 t/ha poultry manure. The application of 5 t/ha poultry

manure combined with 75 kg/ha urea performed better than 150 kg/ha urea as well as

the no fertilized plants. The application of organomineral fertilizers, especially 10 t/ha

poultry manure combined with 75kg/ha was recommended for enhanced maize

production.

Maize requires heavy fertilizer application for optimum yield in terms

of nitrogen derived from chemical or organic fertilizers (Awotundun, 2005). Maize

therefore is high demanding crop for nitrogen than any other cereals (Onwueme and

Sinha, 1991). However, the amount applied depends mainly on the projected maize

yield that appears available and attainable in the locality and the fertility level of the

59

soil as determined by soil test (Shukla, 1990). FPDD, (2002) reported a significant

difference in grain yield of maize due to application of fertilizer (ammonium

sulphate).

Bationo and Lompo (2003), reported significant increase in yield of

maize with application of mineral fertilizer. But yield was higher when mineral

fertilizer was combined with organic manure. Phosphorus up take in maize was

increased with application of poultry droppings in combination with chemical

fertilizer. A tremendous response of maize to foliar application of boron in the

presence of FYM was also recorded. Awotundun (2005), found increased height and

grain yield of pop-corn with application of FYM and NPK fertilizers when applied in

combination. Azeez et al., (2007) also observed good response of maize to application

of crop residues in form of burnt ash. But the response was for a short time. For a

sustained increase in soil nutrient levels and yield of maize, incorporation of ash

should be complemented with mineral fertilizers.

It was reported that maize with combined application of Zn (1.5%) and

NPK fertilizer significantly improved plant height, 1000-grain weight, yield, grain

yield and harvest index as compared to the treatment fertilized only with NPK. Zinc

increased N, P and K uptake and grain yield of maize plants. Foliar-applied Zn

compounds are effective for increasing Zn, Cu and Fe uptake in corn. The optimal

rate of zinc foliar spray for achieving significant grain yield response ranged from 1.0

to 1.5 kg Zn/ha as compared to the treatment fertilized only with NPK. Zinc

treatment increased N, P and K uptake and grain yield (Mona, 2015)

A pot experiment was conducted to compare different organic manures

with NPK fertilizer for improvement of chemical properties of acid soil. The results

60

showed that application of 5 ton/ha of each of the evaluated organic manures and 100

kg/ha NPK 15-15-15 fertilizer improved chemical properties of both acid and nutrient

depleted soils compared with unfertilized soil. Application of different types of

organic manures reduced the acidic levels of both the soils. Application of different

types of organic manures enhanced soil organic C, total N, available P, exchangeable

K and CEC better than NPK fertilizer in both soils. Plant dry matter yield increased

with application of NPK fertilizer compared with compost, poultry manure and cane

rat droppings in both soils. In acid soil, application of NPK fertilizer gave the highest

dry matter yield of 4.77 g/plant while in nutrient depleted soil; application of NPK

fertilizer gave the highest dry matter yield of 5.58 g/plant (Adeniyan et al., 2013).

It was reported that NPK 15:15:15 fertilizer rates have a profound

effect on the overall performance of maize. Application of NPK fertilizer at the

different levels used in this study had significantly effect on the growth and yield of

maize. Fertilizer application level of 400 (60 kg N + 27.16 kg P + 49.80 kg K) kg / ha

is effective for the optimum growth and yield of maize (Ogbomo and Ogbomo,

2009).

Ortiz et al., (2009) evaluate the efficiency of a NPK fertilizer

(8:15:15) with a Zn lignosulfonate (ZnLS) adhered as Zn source for maize plants.

They compared the product in three experimental designs with the same NPK

fertilizer with ZnSO4 adhered and with no Zn adhered. In general, growth chamber

experiments showed that plants treated with NPK + ZnLS presented the highest dry

weight and Zn concentrations in shoots. Also at field experiments, the Zn

concentration in shoots was significantly high in plants treated with NPK + ZnLS.

The grain harvested showed that this treatment gave the highest values in one

61

location, but in the other no significant differences were observed. Although further

research is required, we can conclude that NPK + ZnLS product could be a suitable

source of Zn for maize crops.

Zhong et al., (2014) reported that conducted an experiment o evaluate

the variances of soil physical and chemical, the contents of N, P and K in plant and

maize grain yield. He reported that the soil bulk densities were increased, whereas the

soil porosity, field capacity and pH values were decreased with more N application.

Reasonable N fertilizer amount (241.5 kg/ha) and application at two stages (30% at

sowing and 70% at jointing stage) could significant increase N utilization efficiency

and improve maize yield.

Varghese and Ghosh, (2006) experimented the yield of maize cultivars

( Zea mays L.) Durga hybrid and Jaunpur yellow with or without intercrop of urd

(Vigna mungo L.) under two levels of fertilizers (120, 60, 60 and 140, 90, 70 kg

NPK/ha) and reported that the maximum yield (60.41 q/ha) was found to be with

hybrid maize intercropped with urd when fertilized with 140, 90, 70 kg NPK/ha. The

number and weight of grains cob-1 and 1000 grain weight (248.9g) was also found to

be maximum with 140, 90, 70 kg NPK/ha.

Khan et al., (2014) investigated the response of maize variety (Jalal)

to three phosphorus rates (60, 90 and 120 kg·ha-1) and four nitrogen rates (90, 120,

150, 180 kg·ha-1) for agronomical traits such as number of plant per m2 (NP m2),

plant height (PH), number of leaves plant-1(NLP), leaf area plant-1·cm2 (LAP), fresh

weight of plants kg·ha-1 (FW) and dry weight of plant kg·ha-1 (DW). The results

indicated that application of N @ 180 and P @ 120 kg·ha-1 significantly increased

fodder yield of maize. The linear increase in biomass yield clearly indicated that N

62

was a limiting nutrient factor and that N demand along with P has a positive response.

At higher application rates, N fertilizer significantly increased biomass component,

improved N uptake with increasing nitrogen use efficiency and decreased its losses to

the environment and below plant zone.

Gong et al., (2011) suggested that chemical fertilizer application could

increase C renewal by increasing crop-derived C and accelerating original Soil

Organic Carbon (SOC) decomposition, and that as long as a certain level of crop yield

or aboveground biomass can be achieved, application of chemical fertilizer alone can

maintain or increase SOC level.

Ojima et al, (1994) evaluated the short-term changes in plant

production and microbial activity due to fire and the long-term consequences of

annual burning on soil organic matter (SOM), plant production, and nutrient cycling.

In the short-term, fire enhances microbial activity, increases both above-and

belowground plant production, and increases nitrogen use efficiency (NUE).

However, repeated annual burning results in greater inputs of lower quality plant

residues causing a significant reduction in soil organic N, lower microbial biomass,

lower N availability, and higher C: N ratios in SOM. Changes in amount and quality

of below-ground inputs increased N immobilization and resulted in no net increases in

N availability with burning. This response occurred rapidly (e.g., within two years)

and persisted during 50 years of annual burning. Plant production at a long-term

burned site was not adversely affected due to shifts in plant NUE and carbon

allocation.

It was reported that nitrogen (N) deposition influences both above- and

below-ground communities and influences ecosystem functioning. In this study

63

investigated the responses of soil bacterial diversity to N enrichment at surface (0–

10 cm) and sub-surface (10–20 cm) soils. N addition (>120 kg N ha−1 yr−1) resulted in

a significant shift in bacterial community composition and a decrease in bacterial

OTU richness in surface soil, but the effect on the sub-surface layer was far less

pronounced, even at the highest addition rate (240 kg N ha−1 yr−1). Bacterial OTU

richness was significantly correlated with soil and plant characteristics. The change in

bacterial community composition was due to alterations in soil pH and plant

composition. These results indicated that N fertilization directly affected soil bacterial

richness but indirectly affected bacterial communities through soil acidification and

plant community change, indicating distinct controls on soil bacterial diversity and

community composition. It is also suggest that N availability could be a good

predictor for the loss of soil bacterial diversity under atmospheric nitrogen deposition

(Zeng et al., 2016).

Adediran and Banjoko, (1995) conducted field trials on the response of

maize to nitrogen (N), phosphorus (P), and potassium (K) fertilizers Nitrogen

fertilizer as granulated urea at rates 0–300 kg N/ha, P fertilizer as single

superphosphate at rates 0–120 kg P/h, and K fertilizer as muriate of potash at rates 0–

180 kg K/ha were used for the different nutrient combinations. The base rates for N,

P, and K were 100 kg N/ha, 40 kg P/ha, and 60 kg K/ha, respectively. The results

indicated that annual application of the recommended N, P, and K rates to maize

grown under intensive land use system could not produce optimum yield. The highest

response by maize was to N, the optimum rate ranged from 50–100 kg N/ha.

Application of high rates of P and K fertilizers on soils with fairly sufficient nutrient

level showed no significant effect on maize yield. But when P and K were applied at

low rates (20 kg P/ha and 30 kg K/ha), their contents in the leaf and maize yield, in

64

most cases, increased significantly. It is recommended that the N, P, and K doses for

optimum maize yield are 50–100 kg N/ha, 20 kg P/ha, and 0–30 kg K/ha,

respectively.

Admas et al, (2015) investigated the effects of combined application of

organic and inorganic fertilizers on yield and yield components and nutrient contents

of maize, which were conducted on Nitisols (acidic soils) for two consecutive

cropping seasons at northwestern highlands of Ethiopia. The experiments were laid

down in RCBD as factorial combinations of three levels of N (0, 60 and 120 kg N ha-

1), compost (0, 5 and 10 tn compost ha-1) and S (0, 15 and 30 kg S ha-1). The highest

mean grain yield, dry biomass, plant height, grain number per cob, cob weight,

thousand seed weight, N concentration in leaf and grain (7.9, 22.4 t ha-1, 2.52 m, 486,

0.44 g, 492 g, 3.25 and 1.4%) were observed in plots treated with fertilizer

combinations of 120 kg N ha-1, 10 t compost ha-1 and 15 kg S ha-1, respectively. These

studies showed that incorporation of compost with inorganic N and S fertilizers for

maize enhanced grain yield by adding nutrients.

It was reported from the comparative study on the effect of organic

manure (cow dung) and inorganic fertilizer (N.P.K) on the growth of maize (Zea

Mays L.) that maize plants treated with N. P.K fertilizer were significantly taller than

those treated with cow dung and those of control. Mean number of leaves, stem

diameter, shoot and root dry weight were higher with N.P.K fertilizer but showed no

significant difference (P>0.05) from those grown with cow dung manure. Growth

indices of maize plants to which fertilizer N.P.K was applied showed no significant

(P>0.05) increase than the cow dung. It is recommended that cow dung manure can be

65

used in the absence of N.P.K fertilizer considering the cost and associated

environmental effect of the later (Wisdom et al., 2012).

It was also reported that from the study of comparative efficiency of

organics and biofertilizers on growth and yield of maize (Zea mays L.) during Kharif

season using maize cultivar Nithyashree (NAH 2049) shows that the treatment

having recommended dose of NPK + Azotobacter chroococcum + Bacillus

megaterium + Pseudomonas fluorescence + enriched compost has highest plant height

at 30, 60, 90 days after sowing and at harvest (120 days) (31.70, 180.93, 186.07 and

188.13 cm respectively). The highest total dry matter production at harvest (375.80 g)

and yield parameters like Weight of cob (207.63 g), Grain yield per plant (158.93 g),

Grain yield per ha (54.53 q) and Test weight of seeds (33.10 g) was also found highest

in this treatment and available nutrient content in soil after crop harvest i.e., nitrogen

(185.40 Kg ha-1), phosphorous (38.83 Kg ha-1) and potassium (181.47 Kg ha-1) was

also found highest in the same treatment combination (Umesha et al., 2014).

From an experiment conducted to compare the effect of three different

tillage regimes i.e. deep, conventional and zero and four fertilizer levels viz., control

100-50-50, 150-75-75 and 200-100-100 NPK kg ha-1 on the spring maize, Memon et

al., (2013) reported that there was significant differences in maize emergence

percentage, plant height, grains cob-1 , 1000-grain weight and grain yield due to tillage

practices and various fertilizer levels, between tillage practices. However, the NPK

ratio of @ 200-100-100 kg ha-1 and deep tillage produced the highest emergence

percentage, plant height, grains per cob, 1000-grain weight and grain yield followed

by other fertilizer levels and conventional tillage. The zero tillage plots produced the

low emergence percentage, plant height, grains cob-1 , 1000-grain weight and grain

66

yield. Therefore, considering the environmental conditions, the deep tillage with

recommended dose of NPK performed best and provided more vegetative growth and

grain yield in maize. However, poor-resource farmers can use the medium level of

NPK ratio of 150-75-75 kg ha-1 for getting an economical and successful maize crop.

2.3 Effect of Spacing on maize

It was reported that from the evaluation of three hybrid maize

varieties under three different plant spacing for such growth characters as plant height

and number of leaves. The results obtained 60 days after sowing indicated that hybrid

variety 9022-13 which had mean plant height of 170.0cm and number of leaves of

13.2 was superior to other varieties investigated. With respect to spacing, plants sown

on 75 cm x 15 cm had higher mean height and number of leaves of 176.7 cm and

13.8, respectively which interplay to improve grain yield of maize. (Enujeke, 2013)

It was reported that the steady decline in maize yield can be attributed

to rapid reduction in soil fertility caused by intensive use of land and reduction of

fallow period (DIPA, 2006), failure to identify and plant high yielding varieties most

suited or adapted to each agro-ecological zone (Kim, 1997) and use of inappropriate

plant spacing which determines plant population and final yield (Zeidan et al., 2006).

Iken and Anusa, (2004) recommended an optimum plant population of

53,333 plants/ha for maximum yield of maize and indicated that this is obtainable

using a spacing of 75cm x 25cm at 1 plant per stand or 75cm x 50cm at 2 plants per

stand. Azam et al., (2007) reported that spacing of 75cm x 35cm resulted in

increased grain yield of maize while 75cm x 15cm gave maximum cob weight.

67

Similar report by Allessi and Power (2004) revealed that maize cob weight decreased

with increased plant population.

The high sand content of the soil could be attributed to high content of

quartz in the parent material (Brady and Weils, 1999). The weakly acid nature of the

soil of the area may be traced to the marked leaching of exchangeable bases resulting

from the high rainfall associated with the environment and the dissociation of strong

and functional group in the organic matter (Esu, 2001).

The low organic matter status of the soil could be attributed to the

rapid decomposition of organic matter due to high solar radiation and moisture, these

favour optimum microbial activities in the soil. It could also be attributed to the

annual seasonal bush burning which tend to deplete organic matter accumulation in

the soil (Landor, 1991).

The low level of total nitrogen could be possibly due to low organic

matter content of the soil which contributes about 90-95% of soil nitrogen. It could

also be attributed to leaching of nitrate by torrential rainfall prevalent in the

environment (Olatunji et al., 2007).

The high level of Phosphorus may be attributed to either the history of

land use and cultural practices associated with the land use that do not take much P

nutrient from the soil and the application of P organic or inorganic fertilizers (Nnaji,

2008) or the parent material from which the soil was formed may be rich in P

minerals (Brady and Weils, 1999) or the soil may not be highly acidic as to cause high

level of P fixation (Brady and Weils, 1999; Omokri et al., 2007).

68

It was reported that maize plants spaced 15cm grew taller than other

plants possibly because of increased competition for space, sunlight and available

nutrients (Teasdale 1995; Widdicombe and Thelen 2002). The increased growth rates

and earlier canopy closure of narrow row spaced crops is also attributed to quest for

increased light interception as well as increased availability of soil moisture because

of equidistant distribution of crop plants (Dalley et al., 2006).

Ali et al., (2003), observed that maize plant sown on 15cm spacing had

higher number of leaves than their counterparts which were sown at wider spacing

possibly because of increased growth rate in search for space, sunlight and other

environmental resources. He also reported that competition between maize plants for

light, soil fertility and other environmental factors were markedly increased with

highest population but decreased with lower plant population.

It was investigated that maize plant population of 40000 ha–1 produced

maximum number of kernels per row (32.33). However, 60000 plants ha–1 produced

the maximum number of biomass yield (16890 kg ha–1) and grain yield (2604 kg ha–

1). Therefore, planting density of 60000 plants ha–1 (plant to plant distance of

22.70cm) is recommended for obtaining higher yield of maize (Abuzar et al., 2011).

The plant populations of maize affect most growth parameters even

under optimal growth conditions and therefore it is considered a major factor

determining the degree of competition between plants (Sangakkara et al., 2004). The

grain yield per plant is decreased in response to decreasing light and other

environmental resources available to each plant (Luque et al., 2006). Stand density

affects plant architecture, alters growth and developmental patterns and influences

carbohydrate production. The use of high population increases interplant competition

69

for light, water and nutrients, which may be detrimental to final yield because it

stimulates apical dominance, induces barrenness, and ultimately decreases the number

of ears produced per plant and kernel set per year (Sangoi, 2001).

It was reported that row spacing, were affected on plant dry weight,

dry ear weight, dry leaf and dry stem weight. While the silage yield, ear yield, leaf

yield, plant dry weight and dry ear weight, were affected by nitrogen and showed

significant difference. Potassium had significant difference on plant dry weight, dry

leaf and dry stem weight. The most silage yield (42/23t/ha) and dry plant weight

(13.88 t/ha)obtained from 65cm row spacing that dry plant weight had significant

difference with other row spacing. Amount of 450kg/ha nitrogen was caused the most

silage yield (41/6t/ha) and plant dry weight (13.36 t/ha) that had not significant

difference with usage of 350kg/ha nitrogen. The most silage yield (40/75t/ha)

obtained from 200kg/ha potassium that had not significant difference with other

potassium usage levels. The most plant dry weight (13.36) obtained from 150kg/ha

potassium that had not significant difference with 200 kg/ha potassium usage levels

(Rezaeian et al., 2014).

Sangoi et al., (2001) reported that the reduction of row spacing from

100 to 50 cm increased linearly maize grain yield. The yield edge provided by narrow

rows was higher when maize was sown earlier in the season. Differences in hybrid

cycle and plant architecture did not alter maize response to the reduction of row

spacing.

Decreasing the distance between neighbor rows at any particular plant

population has several potential advantages. First, it reduces competition among

plants within rows for light, water and nutrients due to a more equidistant plant

70

arrangement (Olson and Sander, 1988; Porter et al., 1997). The more favorable

planting pattern provided by closer rows enhances maize growth rate early in the

season (Bullock et al., 1988), leading to a better interception of sun light, a higher

radiation use efficiency and a greater grain yield (Westgate et al., 1997). Secondly,

the maximization of light interception derived from early canopy closure also reduces

light transmittance through the canopy (McLachlan et al., 1993). The smaller amount

of sun light striking the ground decreases the potential for weed interference,

specially for shade intolerant species (Gunsolus, 1990; Teasdale, 1995; Johnson et

al., 1998). Thirdly, the quicker shading of soil surface during early part of the season

results in less water being lost by evaporation (Karlen and Camp, 1985).

Maize plant with inter-row spacing of 0.75m, 0.90m, 1.05m, 1.20m,

1.35m, and 1.50m, with the intra-row spacing of 0.30m, 0.40m and 0.50m were

observed and investigated that the plant height, number of grains per cob, one

thousand grain mass, number of cobs per plant, cob length and grain yield increased

with decrease in plant density. Plant density significantly affected plant height,

number of grains per cob, one thousand grain mass, cob length and grain yield. The

highest grain yield of 2779.80 kg/ha was produced at 16,670 plants ha-1 and the

lowest grain yield of 1073.30 kg/ha was produced at 44,440 plants ha-1 ( Mashiqaa et

al., 2012).

Plant density is dependent on both row width and intra-row spacing,

and under dry land conditions row width plays an important role in determining plant

density. Intra-row spacing should not be too narrow as this can increase competition

between plants and results in yield detrimentally affected. However, under optimum

water and nutrient supply, high plant density can result in an increased number of

71

cobs per unit area, with eventual increase in grain yield (Bavec and Bavec, 2002). Liu

et al., (2004) reported that maize yield differs significantly under varying plant

density levels due to difference in genetic potential.

Lyock et al., (2013) showed that the intercropped maize irrespective

of spacing adopted, were consistently superior to the sole maize crop in dry matter

production per plant, height per plant, number of leaves per plant and leave area per

plant. The best grain yield of 3.78 tonnes/ha was obtained in maize spaced at 75 x 75

cm. The sole ginger crop gave rhizome yield (14.08 tonnes per hectare) was

statistically higher than yields obtained in intercropped treatments. The intercropped

treatments had yield advantages over the sole crop with maize Land Equivalent Ratio

of 23-79%. Therefore, maize at 75 x 75cm in ginger at 20 x 20cm was recommended

as the best intercrop.

Fanadzo et al., (2010) reported that plant population with narrow rows

of 45 cm reduced weed biomass by 58%. Growing maize at 40000 plants ha-1 resulted

in similar green cob weight regardless of inter-row spacing. Cob length decreased

with increase in plant population and with wider rows. Similar grain yield was

obtained regardless of inter-row spacing when maize was grown at 40000 plants ha-1,

but at 60000 plants ha-1, 45 cm rows resulted in 11% higher grain yield than 90 cm

rows. Increasing plant population from 40000 to 60000 plants ha-1 resulted in a 30%

grain yield increase. The study demonstrated that growers could obtain higher green

and/or grain yield by increasing plant population from the current practice of 40000 to

60000 plants ha-1 and through use of narrow rows.

According to Fanadzo, (2007), provided nutrients and moisture are not

limiting, successful cultivation of maize depends largely on the efficacy of weed

72

control. Weed induced losses are highest in smallholder farming and can be as high as

99% in maize Poor weed control decreases water and nitrogen use efficiency, the two

most important inputs to achieving high yields under irrigation (Thomson et al.,

2000).

Liang Yi et al., (2009) reported that the population structure was

improved effectively under wide and narrow row cultivation and the micro-

environment of canopy was improved, the central canopy of light transmission rate

was increased, the competition among individuals were less, the growth of individuals

were better, dry matter accumulation and LAI was increased. This form improved the

initial quantum efficiency of ear leaf, to impel the leaves get the effective utilization

on weak light, and improved the photosynthetic performance of maize leaves, thus

make the yield of maize was improved.

Koli, (1971) reported that increasing the plant population to 21780 per

acre gave highly significant yield over the current adopted 14520 plants per acre.

Generally the higher populations gave the higher yields. Fertilizer application also

increased yields over the control, but high fertilizer rate was not beneficial. The

weight of cob per plant decreased with increasing population. Fertilizer application

increased yield but not significantly. Perhaps it may be more advantageous, in the

forest zone, to use closer spacing such as 2 ft x 1 ft on a fertile land as the evidence

suggests that in a year with fair rainfall distribution, and with planting done at the

optimum time, the increase in yield over wide spacing might be highly significant.

Ibeawuchi et al., (2008) reported that the highest dry maize grain yield

was obtained in the hybrid varieties using plant spacing of 25 x 75cm while the lowest

yield was obtained in the local maize type with plant spacing of 100 x 100cm. The

73

trend observed in the other plant attributes measured such as the plant height and the

Dry Matter Accumulation (DMA) showed that the hybrid maize varieties performed

significantly better than the local ones and had higher nutrient efficiency and

conversion rate than the local cultivars although the yield was predicated on plant

population. It was also recommended that maize sole using plant spacing of 25 x

75cm was the best recommendation for optimum maize grain yield in the field and an

improvement of the local maize cultivars genetically for sustainability and food

security purposes.

The experiment conducted with the maize hybrids Pioneer 3025,

Cargill 707, Cargill 922 and Baber using plant to plant spacing of 15, 25, 35 and

45cm showed that number of cobs per plant, cob weight, grain yield (kg ha-1) and

harvest index were significantly affected by hybrids. Hybrid Pioneer had significantly

higher number of cobs plant-1 (1.14), cob weight (324g), grain yield (3275kg ha-1) and

higher harvest index (24) as compared with other hybrids. Various spacing had

significantly affected cobs/m², grains cob m-1, cob weight and biological yield while

the effect on other parameters was non-significant. Spacing of 15cm had significantly

more number of cob per m² (10), lower grains cob-1 (343), lowest cob weight (227g)

but higher biological yield (15691kg ha-1). Interaction of hybrid Pioneer and 25cm

give highest grain yield ha-1 (Azam et al., 2007).

The experimental result of the photosynthetic characteristics,

chlorophyll fluorescence parameter and yield of waxy maize under the different

planting densities indicated that the planting density of 6.00×104 plants/hm2 was

beneficial to the improvement of Pn,ε,Fv/Fm,ΦPS and qP; and reduction of Rd and

NPQ. The ratio of maize kernel at higher level showed significant to the planting

74

density affecting the photosynthetic characteristics, chlorophyll fluorescence

parameter and yield of waxy maize and there was positive relationship between the

photosynthetic characteristics of the population and maize yield (Wei, 2009).

The study of Jinhai 5 and compact maize Zhengdan 958 showed that

with the increasing of density, plant height was increased, stem diameter and ear

diameter was decreased, ear was shorten, rare top length, No. of ear nod, ear height

was increased, brace root number and total root number was decreased, the rate of

root dry weight was increased within farming layers, population dry matter

accumulation was increased and plant dry matter accumulation presented the opposite

trend, ear linage, kernels per ear,100-kernels weight, double-ear rate, plant yield was

decreased, yield was increased and decreased successively. The relation between yield

and density of Jinhai 5 was Y=-625.67x2+9 044.5x-18 530,optimal plant density was

7.0×104-7.5×104 plants/ha, the relation between yield and density of Zhengdan 958

was Y=-375.67x2+6 410x-13 043,optimal plant density was 8.5×104-9.0×104

plants/ha. It was also revealed that the number of brace roots and total roots could be

used as an indicator for plant dry weight and yield (Li et al., 2008).

The study on the effects of density on photosynthetic physiological

characteristics and yield of maize with Langyu No.6 and Nongda 108 showed that

chlorophyll content , soluble protein content and dry weight per plant dropped by

density increasing, leaf area index, population dry weight, leaf area duration and crop

growth rate increased with increasing density. The effect was more significant in post-

stage than that in earlier-stage. The response to density of Langyu No.6 was more

slowly than that of Nongda 108, both single plant and population characteristics,

which showed that Langyu No.6 density-resistant was more tolerance than Nongda

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108. The suitable planting density of Langyu No.6 and Nongda 108 were 67 500

plants/ha and 60 000 plants/ha respectively. (Ming et al., 2007)

Jing et al., (2009), reported that the population structure of maize was

improved effectively under wide and narrow row cultivation, and the micro-

environment of canopy was improved, the central canopy of light transmission rate

was increased, the competition among individuals were less, the growth of individuals

were better, dry matter accumulation was increased. This form improved the initial

quantum efficiency of ear leaf to impel the leaves get the effective utilization on weak

light and improved the photosynthetic performance of maize leaves, thus make the

yield of maize improved.

The three plant population densities (6.75×104, 8.25×104, 9.75×104

plants/ha) of two summer maize cultivars DH618 and DH605 showed that planting

density had a marked improvement on canopy apparent photosynthesis, canopy

photosynthesis ability and grain yield which ensure the accumulation of

photosynthetic products. Nevertheless net photosynthesis rate decreased along with

the density increased. DH618 had a higher grain-yield than DH605 under the

condition of 10 days early harvest. Both the two cultivars reached maximum

production under the density of 97 500 plant/ha, 13 840 kg/ha and13 080 kg/ha,

respectively. Besides, lodging rate of DH605 was dramatically higher than DH618

(Wang et al., 2015).

Early studies indicated that improved plant spacing uniformity has no

significant effect on grain yield (Erbachetal.,1972; Muldoon and Daynard,1981). In

contrast, other research has demonstrated that non-uniform plant spacing may reduce

grain yield. Krall et al., (1977) reported a significant decrease of 84 kg ha-1 in grain

76

yield for each centimeter increase in SD of plant spacing. Vanderlip et al., (1988)

found that grain yields decrease when SD values exceeded 6 cm. Nielsen (2001)

stated that corn grain yields decrease an established average of 62 kg ha-1 for each

centimeter increase in SD of plant spacing when SD is greater than 5 cm. He also

reported that the rate of yield loss with increasing SD is not constant but varies among

locations in Indiana from 30 to 110 kg ha-1. A more recent on-farm study undertaken

by Doerge and Hall (2001) indicated an average increase in grain yield of 84 kg ha-1

for every centimeter improvement in SD of within-row plant spacing.

According to Muranyi (2015), the optimal plant densities of the

hybrids were different in the two studied crop years: in 2013, regarding the treatments

set with the row distance of 45 cm, increasing plant densities resulted in higher yields,

while in 2014, the yield showed decreasing tendency parallel to the increasing plant

densities, that is confirmed by the fact that plant densities of 50 000 and 65 000 plants

ha-1 proved to be more favourable. Regarding the treatments with a row distance of

76 cm, hybrids obtained their yield maximums by 80 327 plants ha-1 in 2013, while in

the vegetation of 2014, by higher plant density (85 845 plants ha-1).

Roekel and Coulter, (2011) determined a close relationship between

maize yield and plant density. The studied hybrid produced maximal yield by a plant

densities of 81 700 plants ha-1 or even higher. Berzsenyi and Lap, (2005) have also

found that optimal plant density varied between 67 483 and 70 161 plants ha-1

regarding the average of the involved hybrids. According to Shapiro and Wortmann

(2006) a yield increment of 4% could be produced by decreasing the row distance

from 76 cm to 51 cm. Mohseni et al., (2013) confirmed that the increase of plant

77

density from 60 000 plants ha-1 (9.09 t ha-1) to 80 000 plants ha-1 (11.14 t ha-1)

resulted in a yield increment as well.

Norwood, (2001) reported in hybrid corn that early sowing (April 17)

with population of 60000 plants ha-1 gave lowest yield (22.1 q ha-1) compared to

lower population 30000 plants ha-1 (23.2 q ha-1). Similarly under late sowing (May 6)

with a population of 60000 plant ha-1 gave higher yield (40.2 q ha-1) as compared to

30000 plants ha-1 (26.9 q ha-1).

Lauer and Rankin, (2004) similarly measured the response of plant

grain yield to spacing variability, and attempted to determine if there exists a common

threshold where variability begins to affect that yield. Data was collected over 24

Wisconsin environments from the years 1998 to 2000. From which, they observed

that the standard deviation of plant spatial variability typically ranged from 4 to 17

cm. Their repeated deviating spacing patterns indicated that exceeding a 95%

confidence interval range of 9 to 14 cm incurred by-plant yield reductions. They too

agree that the term standard deviation does not always convey a meaningful

assessment of a stand’s composition regarding how the uniformity variations were

created. However, they stated that the plant spacing variability typically observed in a

producer’s fields does not significantly alter overall grain yield.

Liu et al., (2004) examined the hypothesis absolute plant spacing

uniformity is required to achieve maximum corn yield potential at their research

stations in Ontario. To create spacing non-uniformity, Liu et al., (2004) planted

mixtures of Roundup Ready and conventional corn at 69100 plants ha-1. Stands were

thinned with a glyphosate, [N-(phosphonomethyl) glycine], application at the

vegetative stage V3 resulting in spacing standard deviation values from 6 to 16 cm.

78

When their data was combined over both locations and years, researchers observed no

20 significant grain yield response due to within row spacing variability. Numerically

compared to their “6 cm” control treatment, the slope coefficient of regression

indicated a grain yield decrease of 32.5 kg ha-1 for each 1 cm increase in spacing

deviation. Multiple regression analyses determined that short and long gaps, doubles

and skips explained 77% of the variance in plant spacing standard deviation.

Furthermore, they determined each plant-to-neighbor arrangement’s contributable

weight to the spacing standard deviation values which follow: long gap > multiple

plant clusters > short gap > doubles.

Martin et al., (2005) studied by-plant yield variation instead for on-

farm production environments ranging from Argentina to Nebraska. The data

collected described plant-to-plant 21 grain yield in terms of standard deviation,

coefficient of variation, and yield range. Their results showed that the standard

deviation of corn plant productivity increases with increasing final yields; however,

the coefficient of variation for those consecutive within-row plant yields was

negatively correlated with mean grain yield. The range of by-plant yields also

increased with average corn grain yields. Researchers proposed that the common

components that create within-row stand variability (planting depth, tillage,

compaction, moisture, etc.) also influence plant-to-plant productivity variations.

Their research also suggests that precision yield monitors are limited in their ability to

accurately describe yield variability over a large standing area. Furthermore, yield

may then only be averaged over 0.5 to 0.6 meters of row length, so as to adequately

describe the variation of by-plant yields.

Hashemi et al., (2005) examined how crowding stress, resultant to

field populations and variable within-row spacing, influenced the response of corn

79

yield and its components. Their study was conducted during 1986, 1987, 1998, 1999

and 2000 at locations in Massachusetts and Iran. Hybrids were overplanted and hand

thinned to densities ranging from 2 400 to 120 000 plants ha-1. Crowding

comparisons were made against the lowest planted population as it was assumed to

lack any measurable plant-to-plant competition. Kernel weight declined as population

increased from 30 000 to 120 000 plants ha-1 between 9 and 21%; however, as

population increased, the decline in yield was mostly due to kernel number reduction.

The harvest index measurements indicated that plant-to-neighbor crowding had little

influence over assimilate partitioning. Their research concluded that plant-to-plant

competition occurring at V5 to anthesis and anthesis to grain filling had the greatest

negative effect on final grain yield (8 to 21% and 6 to 22%, respectively).

As with stand density, nitrogen fertilization is a management factor

that markedly affects corn crop development. Research by Rossini et al., (2011) in

Argentina sought to describe the influence that stand densities and variable N-rates

have over development regarding plant growth rates, ear growth rates and number of

kernels per plant during the early-reproductive and silking development stages. Two

hybrids, defined by their crowding tolerance, were cultivated with different

combinations of stand density (60 000, 90 000 and 120 000 plants ha-1) and N supply

(0 and 200 kg. of N ha-1 fertilized at V6). Analysis of their density by contrasting

Nitrogen-supply response data indicated that increasing crowding and competition for

limited resources causes reductions to plant biomass and kernel number per plant (39

to 72% loss of kernel number). Interestingly, fertilization with Nitrogen reduced

plant-to-plant variations in kernel number and biomass partitioning, suggesting that

this management practice could reduce the effects provoked by accidental non-

uniformly spaced plant stands.

80

Chapter – III

STUDY AREA

3.1 Geographical location

3.1. Mizoram

With a geographical area of over 21,087 Sq km and perched on the

high hills of the North Eastern part of the country, Mizoram possibly has the most

difficult terrain, over 80% of the total geographical area being hilly and with steep

hills separated by rivers flowing North to South, thus, creating innumerable hurdles in

intra- state as well as inter-state communication. This landlocked area is bounded by

foreign countries on all sides except for a small stretch that rubs shoulder with Assam,

Manipur and Tripura. Its international border, which is about 722 km, is almost 3

times longer than its border with the mainland. Mizoram lies between 21030’N –

23015’N Latitudes and 92016’E – 93026’E longitudes (Rintluanga, 1994). Mizoram is

bounded on the North side by Cachar district of Assam and Manipur state; on the

East and South by Chin hills of Myanmar; on the west by Chittagong hill tracts of

Bangladesh and Tripura.

The state is divided into eight administrative districts, viz., Aizawl,

Champhai, Kolasib, Mamit, Lunglei, Serchhip, Lawngtlai and Saiha (Fig.3.1). About

57.8 percent of the population depends on agricultural products and practice jhum

cultivation (Anon., 2004a). As per 2011 census, Mizoram has recorded a population

81

of 1,091,014 consisting of 552,339 males and 538,675 females, a sex ratio of 975

females to 1000 males.

Figure 3.1: Map of the districts in Mizoram State showing the location of Aizawl city.

82

The topography of Mizoram is, by and large, mountainous with

precipitous slopes forming deep gorges culminating into several streams and rivers.

Almost all the hill ranges traverse in the North – South direction. The eastern part of

Mizoram is at a higher elevation compared to the western part. The average height of

the hill ranges is around 920m, although the highest peak, the Blue mountain

(Phawngpui) goes up to 2165m.

3.1.2 Aizawl

Aizawl is the capital as well as the largest city of Mizoram. It is

located north of the Tropic of Cancer in the northern part of Mizoram and is situated

on ridge 1132 m (3715 ft) a.m.sl., with the Tlawng river valley to its west and the

Tuivawl river valley to its east. Summer temperature ranges from 20 – 30oC, and

winter 11 – 21oC. The geographical area of Aizawl is 3,576 sq km and as per the

2011 census a population of 404,054.

3.2 Climate and weather

3.2.1 Mizoram

Mizoram enjoys a moderate and pleasant climate. The temperature

varies from 90C to 240C during winter and 240C to 320C during summer. The climate

is pleasant in the months of October and November (190C to 250C). The upper part of

the hills are predictably cool, during the summer, while the lower reaches are

relatively warm and humid. Storms break out during March- April, just before or

around the summer. The entire Mizoram comes under the direct influence of the

South west monsoon receiving an annual average rainfall of 2095mm in the year

2009. The rainy season normally starts from June and continues up to September and

83

the rainfall is more or less evenly distributed throughout the state excepting the South-

western parts that generally receives slightly higher rainfall (Anon., 2011).

3.3 Soils

3.3.1 Mizoram

The soils of Mizoram are dominated by sedimentary formation. These

are generally young, immature, mostly developed from parent materials such as

fereginous sandstones and shale. The soils of Mizoram are classified into three orders

such as ultisols, inceptisols and entisols (Sarkar and Nandy, 1976; Singh and Dutta,

1989). The soils in the hills are collocium deposit and in plain areas alluvial deposits

are predominant. The soils as a whole are well drained except in few valley flat lands.

The soils in general have low inherent fertility viz. bases and mineral reserves. The

soils in the hills are strongly acidic in reaction, whereas the soils in alluvial deposits

are less acidic in nature (Anon., 1991a). Analysis of soil samples from different places

in Mizoram indicates that available manganese, copper and iron are adequately

available except zinc. (Anon., 2004b).

The surface soils of the hilly terrains of Mizoram are dark, highly

leached and poor in bases, rich in iron and acidic with pH values ranging from 4.5 to

6.0. The soils are well-drained, deep to very deep, rich in organic carbon, low in

available phosphorus content and high in available potash. The surface soil textures

are loam to clay loam clay content increasing with depth. The percentage of clay, silt

and sand within 50cm of the surface in most cases are 20-30 percent and 25-45

percent respectively. The pH and organic C content mostly decrease with depth. The

base saturation above a lithic or paralithic contact is mostly is low which is below 35

percent (Anon., 1991a). They are capable of providing substantial oxygen supply for

84

plant growth and have capability to retain moisture and maintain supply through the

growing seasons of most crops.

3.4 Forest and vegetation

3.4.1 Mizoram

The state of Mizoram falls under the tropical semi-evergreen belt.

However, due to reduced jhum cycles it is replaced by bamboo interspersed with

secondary forests. The state is divided into 12 forest divisions falling under three

territorial circles. The forest of Mizoram are governed by the Mizoram (Forest) Act,

1955. Commercial utilization of the forests is prohibited but small felling is permitted

for the use of bona fide locals to meet their needs (State of Forest Report, 2006).

The forests are divided into Protected areas, reserve forest and

unclassified forests. According to State of Forest Report, open forest occupies

61.18%, scrub 0.01%, moderately dense 28.87%, very dense 0.64% and non-forest

9.3% to the total geographical area of the state. Area under recorded forest is 16,717

km2 (ISFR, 2011). The reserved- forest covers 6465 km2 and the Protected forest

coves 941 km2 (Anon., 2008a).

Various authors have classified the vegetation of the state. Based on

Champion and Seth’s classification (1968) the following types of forest are found to

be present in the state:

(a) Tropical wet-evergreen forests (up to 900 m)

(b) Tropical semi-evergreen forests (900-1500 m)

(c) Montane sub-tropical pine forests (1500-2158 m)

85

Figure 3.4: Map of Mizoram State showing open and dense forest. (ISFR, 2011)

86

Tropical Wet -Evergreen forests are found in the Southern and Western

parts of Mizoram. The common timber species found in these areas are Dipterocarpus

turbinatus, Artocarpus chaplasa, Terminalia myriocarpa, Duabanga sonneratoides,

Michelia champaca growing in association with undergrowth (Anon., 2003).

Tropical semi-evergreen covers the central bio-geographic zone and

the coverage is approximately 50 percent of the total geographic area. The common

tree species are Michelia champaca, Schima wallichi, Gmelina arborea, Catanopsis

tribuloidies etc. Bamboo species like Melocanna baccifera and Dendrocalamus

species and canes are abundant, especially in shady and low lying areas (Anon.,

2003).

The Montane sub-tropical pine forest occurs in the eastern fringes

bordering Myanmar and constitutes about 24 per cent of the total geographical area.

The common tree species are Pinus kesiya, Rhododendron arboretum, Quercus

serrata, Quercus griffithii, etc. (Anon., 2003).

3.5 Landuse Pattern and cropping system in Mizoram

Land within Mizoram, like some other states of North east, is in the

customary ownership of the communities. Village lands falling within the jurisdiction

of villages are controlled by the Village Council (s) and land distribution is done as

per the customary practice to the villagers for jhumming and other farming activities.

The landuse pattern of the state has been affected primarily by land capability as

determined by characteristics of micro and mini watersheds. Besides, several social

legal factors such as land tenure system etc. also affect the landuse pattern.

87

Agriculture is the main stay for about 60 per cent of the population of

Mizoram. Of the total area only 21 per cent is put on the paddy/ seasonal crops. As

high as 63 per cent of the total crops area is under jhum cultivation. The crops grown

in the jhum are mixed. The principal crop is paddy and others are maize, cucumber,

beans, arum, ginger, mustard, sesame, cotton etc. There is vast scope for cultivation of

tapioca, sugarcane, cotton, pulses and oil seeds in the State. Oil seeds crops like

sesame, mustard and soyabean are growing well in the state. Paddy occupies almost

50 per cent of the total cropped area and more than 88 per cent of the total area under

food grains (Anon., 2010).

88

CHAPTER IV

MATERIALS AND METHODS

4.1 Experimental Site

The experiment was conducted at Edenthar area which is at the outskirt

of Aizawl, the capital city of Mizoram State. The altitude is about 493m from MSL

with geographical coordinates of 23.754149° N and 92.714610°E. The hill slopes have

the soil orders of ultisols with sandy clay loam texture. The average annual rainfall in

this area is 2150 cm. The experiment was carried out in the month of March to July in

the year 2010. The surface soils are dark, highly leached and poor in bases, rich in

iron. pH and organic carbon content decrease and clay content increases with depth.

4.2 Experimental Design and treatments

The experiment was designed using Randomized Block Design (RBD)

with three replications. There was 12 sub-plots and each of the sub-plot was 4m x 3m

(12 sq.m) and each sub-plot is separated by 1 metre width buffer zone. Each

replication covered an area of 210 sq. metre.

Experimental Design : Randomized Block Design. (RBD)

No.of Replications : 3 (three)

Sub-Plot size : 4m x 3m ( 12 sq.m)

No.of Sub-Plots : 12 sub-plots under each replication (36 nos.)

Area of one plot size : 210 Sq.m

Area of total (3) plot size : 630 sq.m

Crop species : Zea mays L

Treatments : 12 treatments

89

4.3 Experimental Layout

R1: 4m

3M

R2 :

R3:

:

NS3F3S1F0 S3F0

1M

S2F2 S2F0

SS3F2

S3F1

S1F2 15M

S2F1S2F3

ES1F1S1F3

S1F1

S3F2

S1F2

S3F3

S3F1

S1F0

47M

S3F0

S2F1

S2F2

S2F0

S1F3

S2F3

S2F1

S3F0

S3F3

S1F0

S2F0

S1F1

S1F2

S3F2

15M

S3F1

S2F3

S1F3

S2F2

15M

90

Figure 4.1: Location of the experimental site at Edenthar showing the treatment plots

of the experimental block.

90



90



91

4.4 Treatment details

Three jhum cycle sites viz. 2 years jhum cycle (2JC), 3 years jhum

cycle (3JC) and 5 years jhum cycle (5JC) were selected, which located adjacent to

each other within an area of 2 acres to rule out the difference in environmental

parameters. Three levels of nitrogen (N), phosphorus (P) and potassium (K) fertilizer

doses and control (without NPK) were applied against three different spacing as table

below:

Table 4.1: Table showing combination of spacing and fertilizer treatment plots

Fertilizer

Treatment

NPK Doses (kg/ ha) Spacing Treatment

N P K Row to row Plant to plant

S1F0 0 0 0 55 20

S1F1 80 40 20 55 20

S1F2 100 50 30 55 20

S1F3 120 60 40 55 20

S2F0 0 0 0 75 20

S2F1 80 40 20 75 20

S2F2 100 50 30 75 20

S2F3 120 60 40 75 20

S3F0 0 0 0 60 25

S3F1 80 40 20 60 25

S3F2 100 50 30 60 25

S3F3 120 60 40 60 25

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4.5 Application of NPK fertilizer

A mixture of Urea (N), Single Super Phosphate (P) and Muriate of

Potash (K) is applied in the field in three different doses such as 120, 60, 40 kg/ha;

100, 50, 30 kg/ ha; 80, 40 20 kg/ha respectively at two split doses in the field before

tillering and after sowing.

4.6 Details of collection of Data

4.6.1 Soil sample collection

Prior to land preparation soil samples were collected from 12 locations

in each replication from three jhum cycle sites by using spade from a depth of 0- 30

cm on one day before the start of the experiment . Soil samples were collected and

packed in the polythene bag. The three jhum plots were slashed and burnt before the

experiment. The soil samples were serially registered giving all the necessary

information mentioning the sample number, place of collection, depth of collection of

samples and site description.

4.6.2 Processing of soil samples

The soil samples were air dried and crushed and passed through sieves

of finer mesh size (Ghosh et al., 1983).

4.6.3 Determination of pH

The pH of the soil samples was measured by the method of soil to water ratio

93

of 1:2. Soil samples of 20 g was taken in a 100 ml beaker to which 40 ml of water was

added. The suspension was stirred at regular intervals for 30 minutes and the pH was

recorded with the help of pH meter.

4.6.4 Estimation of Organic Carbon

The method given by Walkley and Black (1934) was adopted to

estimate Organic Carbon. Soil samples were grounded and completely passed through

0.2mm sieve and 1.00g of it was kept at the bottom of a dry 500ml conical flask. Then

10ml of 1N K2Cr2O7 was pipetted in and swirled a little. The flask was kept on

asbestos sheet. Then 20 ml of H2SO4 (containing 1.25% Ag2SO4) was run in an

swirled again two or three times. The flask was allowed to stand for 30 minutes;

thereafter, 200ml of distilled water was added. Thereafter, 10ml of phosphoric acid or

0.5g Sodium fluoride and 1ml of diphenylamine indicator was added and titrated with

ferrous Ammonium Sulphate solution till the colour flashes from the blue violet to

green. Simulteneously, a blank was run without soil. The result was calculated by the

following method:

Organic Carbon (%) = 10(B-T) x 0.003 x 100

B Wt. of soil

(Where B= Volume (in ml) of ferrous ammonium sulphate solution required for blank

titration; & T= Volume of ferrous ammonium sulphate needed for soil sample).

4.6.5 Estimation of Nitrogen (N) content

The procedure for the analysis of Nitrogen content in the soil samples

was divided into three steps, viz. digestion, distillation and titration.

94

Digestion: 1gm of soil sample was taken in each of Kjeldahl flask for

digestion tube and 10ml Conc. Sulphuric Acid was added in each flask. Also, 3gms of

catalyst mixture (Kjeldahl catalyst) was added in each of digestion tube and the

balance without a soil sample was maintained. Temperature was set at 420oC and it

was digested for approximately 1hr till the sample became green colour. Then, the

digester was switched off and the flask was allowed to cool.

Distillation: Firstly, the conical flask was loaded (with 20ml of 40%

Boric Acid) in the receiver side whch will be pink colour as it contain 3 drops of

Bromo cresol green and Methyl red solution of 5 drops. Then, the digested sample

was loaded for distillation. Again, 40% of NaOH was added slowly in automode in

the order of 10ml each time till the colour changes from bluish green to brown

precipitation and the process time was set for 6 minutes for soil sample. After 6

minutes, the sample colour in a conical flask changed fro pink to green to green

colour which was the end point. The flask was then prepared for titration.

Titration: The distillated was titrated against 0.1N HCl. The titration

was stopped when the colour changed from green to pake pink.

% of Nitrogen = 14 x Titrant value x Normality of acid x 100

1000 x Sample wt.

4.6.6 Estimation of phosphorus

The methods developed by Olsen et al., (1954) and Dickman & Brays

(1940) was followed for the estimation of Phosphorus in the soil samples. 2.5g of the

soil sample was taken in 100ml conical flask and a little of Dargo G 60 or equivalent

grade of activated carbon (free of phosphorus) was added followed by 50ml of

95

Olsen’s reagent. A blank is run without soil. Then the flask were shaken for 30

minutes on a platform type shaker and the contents are filtered immediately through

dry filter paper (Whatman No. 1) into dry beakers or vials.

In the filtrate, phosphorus was estimated calorimetrically by Dickman

and Bray’s procedure (Dickman and Brays, 1940). 5ml of soil extract is pipette into a

25ml volumetric flask to which 5ml of the Dickman and Bray’s reagent was poured

in. The rock of the flask was washed down and the content was diluted to about 22ml.

Therefore, 1ml of the diluted stannous chloride solution was added and the volume

makes up to the mark level. The intensity of the blue colour was measured (using mµ

filter) just after 10 minutes and the concentration of phosphorus was determined from

the standard curve. With each sample a blank was maintained.

4.6.7 Estimation of Potassium

Available Potassium (K) incorporates both exchangeable and water

soluble forms of the nutrient present in the soil. The estimation of K of water soluble

forms was carried out with the help of Flame photometer as suggested by Ghost et al.,

(1983). 5gms of soil sample was shaken with 25ml of normal of Ammonium acetate

(pH 7) for 5 minutes and filtered immediately through a dry filter paper (Whatman

No. 1). First few ml of the filtrate was rejected. Potassium concentration in the extract

was determined in the flame photometer.

96

4.7 Biometrical observations

4.7.1 Growth parameters of maize

i) Plant height (cm): Plant height were recorded in situ at 15, 30, 45 and 60

Days After Sowing (DAS) by randomly selecting 10 plants from each plot

and heights were measured by linear scale from the ground level up to the

flag leaf. The mean values were computed and expressed in cm.

ii) Number of leaves per plant: The number of leaves of 10 tagged plants

from each plot were counted at different stages of 15, 30, 45 and 60 DAS

and the mean number of leaves per plant were recorded.

iii) Plant biomass (gm): The plant aboveground biomass was harvested at plant

maturity stage by cutting at the ground level. The plant material was cut into

manageable size and kept in hot air oven at 70oC until constant weight of

dryness was obtained. The dry plant material was then weighed using digital

weighing balance and expressed in gram (gm).

4.7.2 Yield parameters of maize

i) Number of cobs per plant: The number of cob per plant was recorded

from 10 plants which were randomly selected from each plot and the mean

number of cob per plant were recorded.

ii) Length of cobs: Ten cobs per plot were randomly selected at the time of

harvesting and the length of the cobs were measured and the mean cobs

length were computed and expressed in cm.

97

iii) Number of kernel’s row per cob: From the randomly selected 10 cobs

from each plot, the number of kernels row per cob were counted and the

mean number of row were recorded.

iv) Number of kernels per row: The number of kernels in a row from

randomly selected cobs from each plot were counted and the mean number

were computed.

v) Test weight (1000 grain weight): One thousand filled grains were counted

from the grain sample and their weight were recorded in grams.

vi) Grain yield: The grain yield of maize for each treatment was calculated by

using the formula,

Grain yield (kg/ ha.) = 1 ha. X Yield per plot (kg)

Net area of plot

viii) Harvest Index: The term “harvest index” is used to quantify the yield of a

crop species versus the total amount of biomass that has been produced. The

commercial yield can be grain, tuber or fruit. Harvest index can apply

equally well to the ratio of yield to total plant biomass (shoots plus roots) but

above-ground biomass is more common because root mass is so difficult to

obtain. The harvest index of the maize for each treatment was calculated by

using the formula,

Harvest index % = Economic yield (grains) x 100

Biological yield (Straw + grains

98

4.7.3 Statistical Analysis

The experimental data pertaining to each parameters were analyzed

statistically. ANOVA was performed with the help of SigmaStat 4.0 software and

Costat software.

.

99

Chapter – V

Results

Table 5.1 Monthly rainfall of 2010 showing the rainfall pattern during the

experimental period.

The rainfall pattern showed high rainfall during the experimental period from March

to August, 2010. As maize is a water demanding crop, the experiment was conducted

during the rainy seasons as kharif crop (Table 5.1). In Mizoram the slash and burning

of forest vegetation occurred during the February and mid of March. Sowing of seeds

is done mostly during end of March to May depending on the rainfall.

Table 5.2 Soil properties of 2JC, 3JC and 5JC before land preparation.

0.1 15.8

135197.7

308383.5

282.6

493.8405.7

246.3

15.2 49.2

0100200300400500600

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Rain

falll

(mm

)

Month

Jhum cycles pH OC(%)

P2O5(kg/ha)

K2O(kg/ha)

Total N(%)

Soil texture

2 JC 6.15 1.38 7.56 120 0.26 Sandy clay loam3 JC 6.18 1.67 9.32 145 0.32 Sandy clay loam5 JC 6.24 3.11 11.33 180 0.47 Sandy clay loam

100

5.2 Soil analysis

Soil properties of the three Jhum sites sampled before the land preparation for the

experiment (Table 1) showed soil pH ranging from 6.15 in 2 years jhum to 6.24 in 5

years jhum. Similar trend with lowest values in 2 years jhum and highest 5 years

jhum was also observed in other soil parameters ranging from 1.38 to 3.11 kg/ha in

soil OC content, 7.56 to 11.33 kg/ha in available phosphate, 120 to 180 kg/ha in

available potassium and 0.26 to 0.4 % in total nitrogen content (Table 5.2). Although

slightly higher value in pH and higher content of OC, available phosphate, available

potash and total nitrogen content occurred in longer jhum periods, all the soil in the

three jhum cycles represent poor nutrient content for annual crop plantation.

5.3 Effect of Fertilizer application on growth performance

5.3.1 Plant height at 15 days after sowing:

As mentioned earlier, seeds were sown on 24th March, 2010 during

which summer rain occurred. In response to the immediate rainfall after seed sowing,

sprouting was observed from four days after sowing (DAS) of seeds. Measurement of

plant height at 15 DAS showed significant variations among the fertilizer plots under

each spacing treatment (Figure 5.3.1 & Table 5.3.1). Increased in plant height with

increasing level of fertilizer application occurred in all the fertilizer plots of each

spacing. In 2JC, minimum height of 13.85±0.46cm occurred in F0 plot of S1 spacing

while maximum height of 18.38±0.28cm occurred in F3 plot of S3 spacing. In 3JC, in

all the 3 spacing, minimum height ranging from 14.43±0.53cm to 15.14±0.47cm

occurred in plots without fertilizer application where as maximum height ranging

from 18.54±0.33 cm to 18.88±0.23cm occurred in plots with highest fertilizer

application. In 5JC, the plant height of fertilizer plots under S2 spacing showed

highest range of 14.77±0.34 cm (S2F0) to 19.11±0.19cm (S2F3).

101

5.3.2 Plant height at 30 DAS

Plant height at 30 DAS showed significant increase from F0 to F3 plots

in S1 spacing in all the jhum cycles. Except in 2JC, the fertilizer plots under S2 and

S3 spacing showed lesser variations in plant height. Comparatively lower plant height

was observed among the different fertilizer plots under highest density spacing of S1

than that S2 and S3. The maximum height of 63.70±1.96cm (S1F3) in 3JC and

79.87±1.15cm (S1F3) in 5JC of the S1 spacing was comparable to the minimum

values of 63.46±1.96 cm (S3F0) in 3JC and 81.30±3.01cm (S3F0) in 5JC of S3

spacing (Figure 5.3.2 & Table 5.3.2).

Unlike 15 DAS, the plant height in 30 DAS showed marked variations

with high significant levels among the jhum cycles and the minimum values occurred

in plots without fertilizer application under highest density spacing in S1F0 ranging

from 43.16±1.95 cm in 2JC to 68.28±1.40cm in 5JC.


With the increase in growth duration, wider range in plant height

among the fertilizer plots in each of the three spacing was observed. The high increase

in plant height from the 30DAS to 45DAS indicated high growth rate of plants during

30 to 45 DAS, and comparative highly growth rate occurred in the fertilizer plots

under S1 spacing. Statistically significant variations were observed among the

fertilizer plots in under each of the three spacing (Figure 5.3.3 & Table 5.3.3). In 2JC,

under the S1, S2 and S3 spacing, the minimum height to the maximum height ranged

from 79.74±1.40 (S1F0) to 101.92±2.01cm (S1F3), 85.64±1.56 cm (S2F0) to

118.50±4.15 cm (S2F3) and, 83.55±3.36 cm (S3F0) to 122.42±6.62cm (S3F3) which

accounted for 27.81%, 38.36%, 46.52%, increase in plant height respectively.

102

Significant response to fertilizer treatment was observed in 3JC ranging from

89.60±3.32cm (S1F0) to 121.09±5.11cm (S1F3) under S1 spacing, 97.83±2.92cm

(S2F0) to 131.67±4.49cm (S2F3) under S2 spacing and, 106.73±2.98cm (S3F0) to

131.26±5.41cm (S3F3) under S3 spacing which accounted for the increase in 35.14%,

34.59%, 22.98% with fertilizer application in S1, S2 and S3 spacing respectively. In

5JC, less significant variation ranging from 142.34±3.56cm (S1F0) to 170.67±4.33

cm (S1F3) was observed in S1 spacing while higher significant difference ranging

from 159.81±3.50 cm (S2F0) to 184.26±3.14cm (S2F3) in S2 spacing and,

153.94±2.40cm (S3F0) to 181.31±3.44cm (S3F3) in S3 Spacing was recorded which

accounted for 19.90%, 15.29%, 17.77% increase from the minimum height.

The inter jhum comparison of each fertilizer plots showed highly significant

difference (P<0.001). In plot without fertilizer application (F0), the increase in plant

height from 2JC to 5JC ranged from 79.74±1.40cm to 142.34cm in S1, 85.64±1.56

cm to 159.81±3.50 cm in S2 and, 83.55±3.36cm to 153.94±2.40cm in S3.

5.3.4 Plant height at 60DAS

The height measurement at 60DAS showed high growth rate between

45 and 60DAS in 2JC and 3JC where around 100% increase in plant was observed. In

2JC, the significant difference in height ranged from 162.23±4.12cm (S1F0) to

184.63±5.14cm (S1F3) in S1 spacing; 185.61±3.38cm (S2F0) to 215.34±2.49cm

(S2F3) in S2 spacing and, 188.32±1.48cm (S3F0) to 212.72±3.29cm (S3F3) in S3

spacing which accounted for %%% increase in height from their respective minimum

height. 3JC also showed similar trend with minimum and maximum plant height

ranging from 165.38±2.10cm in (S1F0) to 212.54±1.36cm (S1F3) in S1 spacing,

103

190.51±5.36cm (S2F0) to 218.72±1.00cm (S2F3) in S2 spacing and, 193.98±2.55cm

(S3F0) to 217.52±2.60cm (S3F3) in S3 spacing (Figure 5.3.4 & Table 5.3.4).

Slower growth rate was observed in 5JC during 45 to 60DAS when

compared with that of 30 to 45DAS period. 5JC also showed similar trend to that of

2JC and 3JC with lowest plant height among fertilizer plots under S1 spacing when

compared with that of S2 and S3. The minimum to maximum plant height ranged

from 182.33±3.84cm (S1F0) to 212.54±1.36cm (S1F3) in S1 spacing, 205.52±2.04cm

(S2F0) to 229.92±0.28cm (S2F3) in S3 spacing and, 206.89±1.42cm (S3F0) to

232.63±1.36cm (S3F3) in S3 spacing which accounted for 16.56%, 11.87%, 12.44%

increase in plant height from the minimum plant height.

Despite of the highly significant difference at 45DAS with high value

in 5JC, the plant height at 60DAS showed lower range with less significant variations

among the three jhum cycles. Similar trend of lowest plant height in 2JC followed by

3JC and highest in 5JC was also observed at 60DAS. The inter jhum comparison of

plant height showed highest increase in

5.3.5 Number of leaves at 15 DAS

Although similar pattern with that of plant height of increasing values

with increasing in fertilizer application was observed in the number of leaves per

plant at 15DAS, there was almost no significant difference among the different

fertilizer plots under different spacing in the three jhum cycles. Number of leaves

showed narrow range among the four fertilizer treatments (F0, F1, F2 and F3) under

different spacing (Figure 5.3.5 & Table 5.3.5).

Comparable values in number of leaves per plant was observed among

the different fertilizer treatments of 2JC, 3JC and 5JC. Except in S1F0, there was no

significant difference in number of leaves among the jhum cycles.

104

5.3.6 Number of leaves per plant at 30DAS

In comparison with the record of 15 DAS, higher significant level was

observed among the fertilizer treatment plots of S1, S2 and S3 spacing. Plants grown

without fertilizer application contain lower number of leaves per plant in all the three

spacing in 2JC, 3JC and 5JC. Plants under highest density (S1) showed lowest

number of leaves ranging from 7.08±0.11 (S1F0) to 7.68±0.08 (S1F3) in 2JC;

7.57±0.02 (S1F0) to 7.92±0.10 (S1F3) in 3JC and, 7.71±0.09 (S1F0) to 8.02±0.08

(S1F3) in 5JC (Figure 5.3.6 & Table 5.3.6).

Among the jhum cycles, lowest number of leaves occurred in 2JC

followed by 3JC and highest in 5JC. Statistically significant (P<0.05) difference was

observed among the three jhum cycles in F0 and F1 fertilizer plots under the S1, S2

and S3 spacings.


At 45DAS, higher significant difference was observed among the

fertilizer treatment plots in S1, S2 and S3 spacings except in 2JC. The increase in

number of leaves per plant was higher during 30 to 45 DAS when compared with the

period of 15 to 30 DAS (Figure 5.3.7 & Table 5.3.7). The minimum and maximum

number of leaves per plant ranged from 9.85±0.31 (S1F0) to 10.87±0.20 (S1F3) in S1

spacing, 10.98±0.25 (S2F0) to 11.59±0.17 (S2F3) in S2 spacing and, 11.13±0.15

(S3F0) to 11.63±0.14 (S3F2)in S3 spacing in 2JC. The fertilizer treatment plots of

3JC showed higher number of leaves per plant than 2JC and the minimum and

maximum value ranged from 11.35±0.04 (S1F0) to 11.79±0.03 (F1S3) in S1 spacing,

11.40±0.03 (S2F0) to 11.80±0.09 (S2F3) in S2 spacing and, 11.45±0.06 (S3F0) to

11.81±0.09 (S3F3) in S3 spacing. Plant of 5JC showed highest number of leaves in

105

each fertilizer treatment plots ranging from 11.79±0.04 (S1F0) to 12.22±0.02 (S1F3)

in S1, 11.84±0.01 (S2F0) to 12.25±0.03 (S2F3) and, 11.82±0.05 (S3F0) to

12.21±0.04 (S3F3) in S3 spacing.


In 2JC, significant difference in number of leaves per plant ranging

from 10.59±0.17 (S1F0) to 11.50±0.09 (S1F3) in S1 spacing, 11.98±0.05 (S2F0) to

12.56±0.02 (S2F3) in S2 spacing and, 12.09±0.06 (S3F0) to 12.55±0.06 (S3F3) in S3

spacing which accounted for 8.50%, 4.48% and 3.80% increase from the minimum

value respectively (Figure 5.3.8 & Table 5.3.8). Surprisingly reduction in number of

leaves per plant from that of 45DAS was observed in most of the fertilizer plots in S1

of 3JC and 5JC. In 3JC, the minimum and maximum values ranged from 10.49±0.36

(S1F0) to 11.17±0.05 (S1F3) in S1, 12.06±0.15 (S2F0) to 12.78±0.34 (S2F3) in S2

spacing and, 12.18±0.11 (S3F0) to 12.99±0.25 (S3F3) in S3 spacing which accounted

for 6.48%, 5.97%, 6.65% increase from the minimum values. In 5JC, the minimum

and maximum values ranged from 10.87±0.34 (S1F0) to 12.34±0.14 (S1F3) in S1

spacing, 12.48±0.28 (S2F0) to 13.68±0.07 (S2F3) in S2 cycle and, 12.27±0.54 (S3F0)

to 13.66±0.05 (S3F3) in S3 spacing which accounted for increase in 13.52%, 9.61%,

11.32% for the minimum values respectively.

5.3.9 Biomass at harvest

Ten plants per replication was harvested at maturity stage at 23rd &

24th July, 2010 for the determination of biomass. The plant dry biomass at maturity

harvest showed significant variations among the different fertilizer plots of S1, S2 and

S3 spacing. Among three spacing, the fertilizer plots of S1 spacing showed much

106

lesser plant biomass ranging from 264.50±17.37gm (S1F0) to 319.50± 13.12 gm

(S1F3) in S1 spacing, 318.50±14.40 gm (S2F0) to 371.50±6.08 gm (S2F3) in S2

spacing and, 316.50±3.97 gm (S3F0) to 374.20±4.09 gm (S3F3) in S3 spacing. Slight

increase in dry biomass per plant from 2JC was observed in 3JC (except S2F0) with

minimum to maximum plant biomass ranging from 267.77±4.91 gm (S1F0) to

322.38±6.39 gm (S1F3) in S1 spacing, 308.55±3.87 gm (S2F0) to 376.03±5.67 gm

(S2F3) in S2 spacing and, 319.66±3.01 gm (S3F0) to 377.08±2.28 gm (S3F3) in S3

spacing. Highest dry biomass per plant was observed in 5JC which ranged from

292.60±4.50 gm (S1F0) to 327.13±5.96 gm (S1F3) in S1 spacing, 335.80±2.75 gm

(S2F0) to 386.11±1.79 gm (S2F3) in S2 spacing and, 337.72±2.78 gm (S3F0) to

390.93±4.39 gm (S3F3) in S3 spacing (Figure 5.3.9 & Table 5.3.9).

The percentage increase in plant biomass from the plot without

fertilizer application to the highest fertilizer application in S1, S2 and S3 spacing were

20.79%, 16.64% and 18.23%, in 2JC, 20.40%, 21.87% and 17.96% in 3JC and,

11.80%, 14.98% and 15.75% in 5JC.

Among the jhum cycle, lowest biomass production occurred in 2JC

follow by 3JC and highest in 5JC. Low level of significant difference was observed in

each fertilizer plots of S1 spacing. In S2 spacing, significant difference among jhum

cycles was observed in S2F1 and S2F3. Each fertilizer plots of S3 spacing showed

significant difference (P<0.05 to P>0.001). From the all the fertilizer treatments of the

three jhum cycles, the lowest biomass per plant of 264.50±7.37gm (S1F0) of 2JC to

390.93±4.29gm (S3F3) of 5JC accounted for 47.79% increased in plant biomass.

107

Figure 5.3.1 Effect of fertilizer application on plant height at 15 DAS under differentspacing in 2 years, 3 years and 5 years jhum cycles. Vertical line indicates standarderror.


108

Table5.3.1: Plant height at 15 days after sowing (DAS) under different spacing andfertilizer application levels in 2, 3 and 5 years jhum cycles. Mean ±SEM.

* = P<0.05, ** = P<0.01, *** = P<0.001

Table5.3.2: Plant height at 30 days after sowing (DAS) under different spacing andfertilizer application levels in 2, 3 and 5 years jhum cycles. Mean ±SEM.

* = P<0.05, ** = P<0.01, *** = P<0.001.

S1F0 S1F1 S1F2 S1F3LSD(0.05) S2F0 S2F1 S2F2 S2F3

LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC43.16±1.95

52.88±1.96

56.60±1.70

60.66±2.71

**7.77

48.18±1.90

59.57±2.32

63.62±1.34

66.94±1.81

***7.37

50.87±2.94

61.59±2.94

61.30±1.66

65.69±1.73

*10.71

3JC52.72±1.57

56.83±1.36

61.27±1.87

63.70±1.96

**6.87

61.76±2.21

62.53±1.60

69.63±0.51

71.41±3.18

*2.37

63.46±1.96

64.90±2.43

68.67±1.24

70.44±3.39

ns

5JC68.28±1.40

71.14±2.70

74.67±1.38

79.87±1.15

**6.33

83.79±1.54

82.32±2.09

87.18±1.35

89.38±1.57

ns 81.30±3.01

84.83±3.27

87.69±1.83

89.56±1.57

ns

LSD(0.05)

***9.56

**14.31

***13.4

**16.16

***13.57

***19.78

***6.01

**17.97

***12.59

**19.92

***7.36

***19.12


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC13.85±0.46

15.80±0.11

17.16±0.36

18.13±0.55

***1.26

14.42±0.48

16.78±0.47

17.30±0.34

18.10±0.23

**2.35

14.47±0.67

16.69±0.59

17.96±0.29

18.38±0.28

**1.69

3JC14.43±0.53

16.91±0.16

17.98±0.34

18.54±0.33

***1.63

14.37±0.61

17.19±0.31

18.19±0.29

18.88±0.23

***3.03

15.14±0.47

16.90±0.34

18.26±0.46

18.86±0.44

**1.76

5JC14.90±0.11

16.72±0.54

17.44±0.42

18.62±0.29

***1.82

14.77±0.34

17.06±0.40

18.52±0.51

19.11±0.19

***1.45

16.86±0.17

17.11±0.33

18.13±0.13

18.96±0.13

***0.83

LSD(0.05) ns ns ns ns ns ns Ns

*0.78

*1.72 ns ns ns

109


Figure 5.3.4 Effect of fertilizer application on plant height at 60DAS under differentspacing in 2 years, 3 years and 5 years jhum cycles. Vertical line indicates standarderror.

110

Table 5.3.3 : Plant height at 45 days after sowing (DAS) under different spacing andfertilizer application levels in 2, 3 and 5 years jhum cycles. Mean ±SEM.

* = P<0.05, ** = P<0.01, *** = P<0.001.

Table 5.3.4: Plant height at 60 days after sowing (DAS) under different spacing andfertilizer application levels in 2, 3 and 5 years jhum cycles. Mean ±SEM.

* = P<0.05, ** = P<0.01, *** = P<0.001.


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC162.23

±4.12169.03

±3.84177.50

±5.02184.63

±5.14*15.26

185.61±3.38

195.74±3.36

207.87±2.62

215.34±2.49

***10.13

188.32±1.48

197.45±4.72

206.25±1.92

212.72±3.29

**15.26

3JC165.38

±2.10177.44

±5.60186.50

±4.55196.14

±5.32**18.7

190.51±5.36

200.58±1.64

210.98±2.39

218.72±1.00

***10.40

193.98±2.55

202.05±2.01

209.45±4.19

217.52±2.60

**15.47

5JC183.33

±3.84194.88

±3.47201.41

±4.70212.54

±1.36**17.66

205.52±2.04

212.32±2.92

217.45±2.10

229.92±0.28

***6.80

206.89±1.42

211.03±1.84

217.83±2.27

232.63±1.36

***6.80

LSD(0.05)

**17.95

*17.43

*23.91

*16.39

*15

*11.73 ns

**11.2

**12.91 ns ns

**15.11


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC79.74±1.40

89.46±1.88

97.52±5.89

101.92±2.01

**12.46

85.64±1.56

100.03±3.37

112.10±4.15

118.50±4.15

***12.06

83.55±3.36

98.28±2.67

115.34±3.51

122.42±6.62

***14.72

3JC89.60±3.32

101.63±1.61

109.35±1.43

121.09±5.11

***11.73

97.83±2.92

103.21±2.47

118.93±5.17

131.67±4.49

**15.72

106.73±2.98

111.11±3.35

122.84±2.54

131.26±5.41

**16.11

5JC142.34±3.56

157.08±5.69

163.85±3.57

170.67±4.33

*14.74

159.81±3.50

166.56±2.89

171.34±4.21

184.26±3.14

**11.53

153.94±2.40

168.37±4.06

175.33±3.48

181.31±3.44

**12.94

LSD(0.05)

***52.74

***55.44

***54.49

***19.16

***12.18

***63.35

***52.4

***52.58

***23.18

***12.83

***52.49

***50.05

111

Figure 5.3.5 Effect of fertilizer application on number of leaves per plant at 15 DASunder different spacing in 2 years, 3 years and 5 years jhum cycles. Vertical lineindicates standard error.


112

Table 5.3.5 : No. of Leaves at 15 days after sowing (DAS) under different spacing andfertilizer application levels in 2, 3 and 5 years jhum cycles. Mean ±SEM.

* = P<0.05, ** = P<0.01, *** = P<0.001.

Table 5.3.6: No. of Leaves at 30 days after sowing (DAS) under different spacing andfertilizer application levels in 2, 3 and 5 years jhum cycles. Mean ±SEM.

* = P<0.05, ** = P<0.01, *** = P<0.001.


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC5.11

±0.035.54

±0.105.56

±0.1115.80

±0.06**0.43

5.29±0.08

5.58±0.10

5.63±0.12

5.76±0.10 NS

5.44±0.10

5.65±0.09

5.66±0.11

5.70±0.10 NS

3JC5.15

±0.085.55

±0.0865.61

±0.095.83

±0.034**0.28

5.23±0.16

5.59±0.10

5.67±0.04

5.84±0.03

*2.45

5.45±0.10

5.62±0.06

5.69±0.07

5.86±0.04

*0.41

5JC5.47

±0.065.59

±0.095.65

±0.105.82

±0.034 NS5.53

±0.115.61

±0.055.68

±0.075.84

±0.03 NS5.58

±0.095.63

±0.085.70

±0.075.85

±0.02 NSLSD(0.05)

*0.32 ns ns ns ns ns ns ns ns ns ns ns


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC7.08

±0.117.60

±0.047.65

±0.087.68

±0.08**0.52

7.13±0.04

7.65±0.06

7.64±0.07

7.71±0.10

**0.51

7.14±0.20

7.67±0.07

7.67±0.08

7.69±0.08

*0.53

3JC7.57

±0.027.69

±0.047.86

±0.097.92

±0.10*0.29

7.64±0.02

7.74±0.03

7.88±0.09

7.94±0.10 ns

7.63±0.02

7.77±0.03

7.90±0.09

7.94±0.10 ns

5JC7.71

±0.097.82

±0.047.91

±0.078.02

±0.08 ns7.76

±0.067.87

±0.027.96

±0.078.03

±0.06*0.20

7.77±0.05

7.89±0.00

7.99±0.07

8.05±0.08

*0.21

LSD(0.05)

**0.48

*0.21 ns ns

***0.5

*0.21 ns ns

*0.49

*0.22 ns ns

113



114

Table 5.3.7: No. of Leaves at 45 days after sowing (DAS) under different spacing andfertilizer application levels in 2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001.

Table 5.3.8: No. of Leaves at 60 days after sowing (DAS) under different spacing andfertilizer application levels in 2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC9.85

±0.3110.13±0.36

10.39±0.07

10.87±0.20 ns

10.98±0.25

11.48±0.15

11.53±0.14

11.59±0.17 ns

11.13±0.15

11.50±0.05

11.63±0.14

11.61±0.03

*0.37

3JC11.35±0.04

11.48±0.09

11.71±0.01

11.79±0.03

**0.23

11.40±0.03

11.57±0.05

11.74±0.02

11.80±0.09

**0.22

11.45±0.06

11.68±0.01

11.78±0.03

11.81±0.09

*0.22

5JC11.79±0.04

11.89±0.02

12.06±0.07

12.22±0.02

***0.15

11.84±0.01

11.92±0.02

12.10±0.10

12.25±0.03

**0.18

11.83±0.05

12.01±0.06

12.11±0.08

12.21±0.04

**0.20

LSD(0.05)

***1.49

**1.34

***0.35

***0.42

*0.86

*0.34

*0.36

*0.44

**0.37

***0.18

*0.47

**0.4


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC10.59±0.17

10.71±0.28

11.25±0.07

11.50±0.09

*0.65

11.98±0.05

12.35±0.05

12.34±0.06

12.56±0.02

***0.21

12.09±0.06

12.34±0.02

12.41±0.04

12.55±0.06

**0.21

3JC10.49±0.36

10.69±0.32

10.97±0.24

11.17±0.05 ns

12.06±0.15

12.44±0.30

12.54±0.37

12.78±0.34 ns

12.18±0.11

12.45±0.33

12.58±0.27

12.99±0.25 ns

5JC10.87±0.34

11.32±0.07

11.98±0.17

12.34±0.14

**1.02

12.48±0.28

12.75±0.31

13.24±0.15

13.68±0.07

*0.76

12.27±0.54

12.80±0.30

13.25±0.18

13.66±0.05 ns

LSD(0.05) ns ns

*0.73

***0.84 ns ns ns

*0.9 ns ns

*0.67

**0.67

115

Figure 5.3.9 Effect of fertilizer application on number biomass production at maturityharvest under different spacing in 2 years, 3 years and 5 years jhum cycles. Verticalline indicates standard error.

Table 5.3.9: Biomass at maturity harvest under different spacing and fertilizerapplication levels in 2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC162.23

±4.12169.03

±3.84177.50

±5.02184.63

±5.14*15.26

185.61±3.38

195.74±3.36

207.87±2.62

215.34±2.49

***10.13

188.32±1.48

197.45±4.72

206.25±1.92

212.72±3.29

**15.26

3JC165.38

±2.10177.44

±5.60186.50

±4.55196.14

±5.32**18.7

190.51±5.36

200.58±1.64

210.98±2.39

218.72±1.00

***10.40

193.98±2.55

202.05±2.01

209.45±4.19

217.52±2.60

**15.47

5JC183.33

±3.84194.88

±3.47201.41

±4.70212.54

±1.36**17.66

205.52±2.04

212.32±2.92

217.45±2.10

229.92±0.28

***6.80

206.89±1.42

211.03±1.84

217.83±2.27

232.63±1.36

***6.80

LSD(0.05)

**17.95

*17.43

*23.91

*16.39

*15

*11.73 ns

**11.2

**12.91 ns ns

**15.11

116

5.4 Effect of fertilizer application on yield parameters

10 plants per replication plot was harvested on 23rd&24th July, 2010 for

the determination of yield parameters Number of cobs per plant was counted and all

the plants irrespective of difference levels of fertilizer application and jhum cycles

produce only one harvestable cob, and the second cob, if produced, was under-

developed and had no commercial value. So, only the first cob was considered in the

yield parameters.

5.4.1 Length of Cob

The plants grown under different fertilizer treatment showed marked

significant difference in S1, S2 and S3 spacing of 2JC and 3JC where as in 5JC,

significant difference was observed only in fertilizer plots under S1 spacing. In 2JC,

the minimum value was observed in F0 plot in S1, S2 and S3 spacing ranging from

14.70±0.17 cm (S1) to 17.50 cm (S3), and the maximum value in F3 plots ranged

from 17.31±0.14 cm (S1) to 19.10±0.31 cm (S3) (Figure 5.4.1 & Table 5.4.1). In 3JC,

the minimum values among S1, S2 and S3 ranged from 16.00±0.40 cm (S1F0) to

18.94±0.18 cm (S2F0) and the maximum values ranged from 18.87±0.18 cm (S1F3)

to 20.62±0.23 cm (S2F3). 5JC showed highest LoC with minimum values of

17.73±0.38 cm (S1F0), 20.66±0.12 cm (S2F0) and 20.65±0.16 cm (S3F0), and

maximum values of 20.16±0.18 cm (S1F0), 22.08±0.31 cm (S2F3) and 22.08±0.39

cm (S3F3).

Highly significant (P<0.01) difference was observed in each fertilizer

treatment plots among the jhum cycles. In S1 spacing, the maximum value of

17.31±0.14 cm (S1F2) in 2JC was comparable with the minimum value of

17.73±0.38 cm (S1F0) in 5JC. Likewise, the maximum value in LoC under high

117

fertilizer application plots of S2 and S3 of 2JC was comparable and slightly lower

than the corresponding minimum values of 5JC.

5.4.2 Kernel row per cob

Although increasing in kernel rows per cob with increasing fertilizer

application was observed in S1, S2 and S3 spacings, statistically significant difference

among the fertilizer treatment plots was observed only in S1 and S2 spacings of 2JC

(Figure 5.4.2 & Table 5.4.2). The maximum Kernel row per cob of 11.05±0.23 of

2JC, 11.45±0.12 of 3JC and 11.99±0.11 of 5JC in S1 spacing was lower than

minimum values of 11.61±0.22 (S2) and 11.74±0.18 (S3) of 2JC, 11.99±0.08 (S2)

and 12.19±0.15 (S3) of 3JC and, 12.63±0.09 (S2) and 12.71 (S3) of 5JC respectively.

Among the three jhum cycles, the difference in kernel row per cob was

statistically significant (P<0.05) in each of the fertilizer treatments with lowest

number in 2JC and increasing with longer jhum cycles.

5.4.3 Number of kernels per row

The number of kernels per row showed statistically significant

(P<0.05) different among the plants grown under different levels of fertilizer

application in all the three jhum cycles except in S2 spacing of 2JC. Evidently lower

number of kernels in each kernel row was observed in the fertilizer plots of S1

spacing when compared with their corresponding plots in S2 and S3 spacings in all

the three jhum cycles (Figure 5.4.3 &Table 5.4.3). Similar to the kernel row per cob,

the maximum number of kernels per row of 27.75±0.18 in 2JC, 30.90±0.10 in 3JC

and 32.90±0.29 in 5JC was lower than that of the minimum values of S2 spacing

(31.63±0.17, 35.01±0.33 and 36.67±0.19 in 2JC, 3JC and 5JC respectively) and S3

spacing (31.42±0.10, 34.51±0.11 and 36.70±0.38 in 2JC, 3JC and 5JC respectively).

118

The minimum and maximum values among all the fertilizer and

spacing treatment plots ranged from 26.24±0.48 (S1F0) to 33.44±0.34 (S3F3) in 2JC,

28.96±0.34 (S1F0) to 36.11±0.14 (S2F3) in 3JC and, 31.63±0.19 (S1F1) to

38.58±0.22 (S2F3) in 5JC.

The number of kernels per row among each fertilizer treatment plots

showed highly significant (P<0.001) variations of lowest values in 2JC and highest

values in 5JC. In S1 spacing, the number of kernels per row ranged between

26.24±0.48 to 27.75±0.18 in 2JC, 28.96±0.34 to 30.90±0.10 in 3JC and 31.63±0.19 to

32.90±0.29 in 5JC. Fertilizer plots in S2 and S3 spacings showed comparable values

ranging from ca. 31 to 33 in 2JC, 34 to 36 in 3JC and 36 to 38 in 5JC.

5.4.4 Number of kernels per cob

Similar to the previous yield parameters of kernel rows per cob and

number of kernels per row, the number of kernels per cob showed marked difference

among the fertilizer plots as well as among the different spacing. Fertilizer plots of

2JC showed highly significant difference ranging from 270.44±7.03 (S1F0) to

306.59±6.78 (S1F3) in S1 spacing, 368.47±3.82 (S2F0) to 410.65±3.14 (S2F3) in S2

spacing and, 368.99±5.35 (S3F0) to 417.93±2.61 (S3F3) in S3 spacing (Figure 5.4.4

& Table 5.4.4). 3JC also showed similar trend ranging from 317.57±14.90 (S1F0) to

353.72±4.86 (S1F3) in S1 spacing, 414.76±3.48 (S2F0) to 460.25±4.50 (S2F3) in S2

spacing and, 420.62±6.33 (S2F0) to 456.77±5.34 (S3F3) in S3 spacing. 5JC showed

highest number of kernels per cob in each fertilizer treatment ranging from

373.21±4.22 (S1F0) to 394.36±4.96 (S1F3) in S1 spacing, 462.95±1.90 (S2F0) to

506.11±5.16 (S2F3) in S2 spacing and, 469.83±2.47 (S3F0) to 508.71±0.72 (S3F3) in

119

S3 spacing. The maximum values of kernels per cob in each of the jhum cycles were

lower than the minimum values of the fertilizer plots of S2 and S3 spacings.

The number of kernels per cob in each fertilizer treatments showed

highly significant variations (P<0.001) with lowest values in 2JC followed by 3JC and

highest in 5JC. The increase in number of kernels per cob from 2JC to 5JC in each

fertilizer plot ranged from ca. 70 to 100.

5.4.5 Test weight

Test weight, that is the weight of randomly selected 1000 seeds

showed significant variations (P<0.05) among the fertilizer plots in all the three jhum

cycles (Figure 5.4.5 & Table 5.4.5). In 2JC, the test weight ranged from 255.33±2.60

gm(S1F0) to 275.67±2.40 gm (S1F3) in S1 spacing, 275.33±3.18 gm (S1F0) to

303.00±1.16 gm (S2F3) in S2 spacing and, 277.00±2.08 gm (S3F0) to 303.28±1.36

gm (S3F3) in S3 spacing. In 3JC, the minimum and maximum values of the fertilizer

plots ranged from 263.67±1.86 gm (S1F0) to 281.67±1.45 gm (S1F3) in S1 spacing,

283.67±1.86 gm (S2F0) to 305.33±0.88 gm (S2F3) in S2 spacing and, 284.67±1.45

gm (S3F0) to 306.00±0.58 gm (S3F3) in S3 spacing. Lower significant variations was

observed among the fertilizer plots of S1, S2 and S3 spacing ranging from

274.20±1.73 gm (S1F0) to 288.73±0.37 gm (S1F3) in S1 spacing, 293.50±3.67 gm

(S2F0) to 309.24±1.92 gm (S2F3) in S2 spacing and, 293.33±2.19 gm (S3F0) to

311.08±1.45 gm (S3F3) in S3 spacing. The increase in test weight from the lowest

weight to the highest weight among the fertilizer plots of S1, S2 and S3 accounted for

7.96%, 10.05% and 9.49% increase in 2JC, 6.83%, 7.64% and 7.49% in 3JC and

5.30%, 5.36% and 6.05% increase in 5JC respectively. The maximum test weight of

120

S1F3 plots in S1 was comparable with the lowest weight of the plots without fertilizer

input (F0) in S2 and S3.

The test weight in each fertilizer plots among the jhum cycles showed

significant variations S1F0, S1F1, S1F3, S2F0, S2F2, S3F0, S3F2 and S3F3. Test

weight increases from 2JC with increase in the period of jhum cycle.

5.4.6 Grain yield

The grain yield in terms of dry weight showed highly significant

(P<0.01) difference among most of the fertilizer treatments. Comparatively lower

grain yield was observed among the fertilizer plots in S1 spacing. Grain yield

increased with increase in fertilizer application as well as increase in the period of

jhum cycle (Figure 5.4.6 & Table 5.4.6). The range of the minimum to the maximum

grain yield in 2JC was 6274.4±105.11 kg (S1F0) to 7683.5±188.8 kg (S1F3) in S1

spacing, 6764.2±127.26 kg (S2F0) to 8294.7±46.24 kg (S2F3) in S2 spacing and,

6812.9±77.69 kg (S3F0) to 8449.9±64.56 kg (S3F3) in S3 spacing which accounted

for 22.46%, 22.63% and 24.03% increase in grain yield. In 3JC, grain yield ranged

from 7614.7±388.7 kg (S1F0) to 9057.8±145.10 kg (S1F3) in S1 spacing,

7842.8±38.07 kg (S2F0) to 9367.9±64.86 kg (S2F3) and, 7983.1±149.79 kg (S3F0) to

9317.7±93.19 kg (S3F3) in S3 spacing which accounted for 18.95%, 19.45% and

16.72% increase in grain yield respectively. Highest grain yield in 5JC among the

fertilizer plots ranged from 8806.7±76.77 kg (S1F0) to 9919.9±103.87 kg (S1F3) in

S1 spacing, 9051.7±30.18 kg (S2F0) to 10435.0±171.47 kg (S2F3) in S2 spacing and,

121

9219.4±85.72 kg (S3F0) to 10549.9±40.29 kg (S3F3) in S3 spacing which accounted

for 12.64%, 15.28% and 14.43% increase in grain yield respectively.

The grain yield was significantly (P<0.001) increased by the increase

the period of jhum cycle in all the fertilizer treatments. The maximum grain yield of

7683.5±188.8 kg (S1F3) in 2JC was lower than the minimum yield of 8806.7±76.77

kg (S1F0) of 5JC in S1 spacing. Similar result was also observed in S2 and S3

spacings where the maximum yield in 2JC was comparatively lower than the

minimum yield in 5JC.

5.4.7 Harvest Index (HI)

Harvest Index which indicates the yield production per gram of

vegetative biomass production showed no significant difference among the fertilizer

treatments in all the three spacings as well as the three jhum cycles. But marked

significant variations (P<0.01) was observed in each fertilizer plots among the jhum

cycles. HI increased with increasing jhum cycles. Low HI <0.27 was observed in all

the fertilizer plots of S1 spacing in 2JC where as high values of >0.40 was observed

in most of the fertilizers plots of S2 and S3 spacings in 5JC.

122

Figure 5.4.1 Effect of fertilizer application on length of cob under different spacing in2 years, 3 years and 5 years jhum cycles. Vertical line indicates standard error.

Figure 5.4.2 Effect of fertilizer application on kernel rows per cob under differentspacing in 2 years, 3 years and 5 years jhum cycles. Vertical line indicates standarderror.

123

Table 5.4.1: Length of cob under different spacing and fertilizer application levels in2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001

Table 5.4.2: No. of Kernel rows per cob under different spacing and fertilizerapplication levels in 2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC14.70±0.17

14.87±0.12

17.31±0.14

15.90±0.31

***1.03

17.48±0.30

18.54±0.21

18.80±0.16

19.07±0.36

*1.06

17.50±0.36

18.64±0.33

18.98±0.17

19.10±0.31

*1.14

3JC16.00±0.40

17.07±0.19

18.64±0.25

18.87±0.18

***1.06

18.94±0.18

19.69±0.25

20.35±0.35

20.62±0.23

**0.93

18.90±0.12

19.79±0.23

20.43±0.36

20.58±0.24

**0.89

5JC17.73±0.38

18.62±0.30

19.40±0.09

20.16±0.18

**0.88

20.66±0.12

21.32±0.37

21.64±0.38

22.08±0.31 NS

20.65±0.16

21.42±0.38

21.75±0.38

22.08±0.39 NS

LSD(0.05)

**1.3

***1.55

***0.75

***1.29

***1.46

**1.14

**1.28

**1.46

***1.4

**1.14

**1.31

**1.48


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC10.30±0.08

10.32±0.12

10.95±0.15

11.05±0.23

*0.62

11.61±0.22

12.10±0.07

12.18±0.15

12.37±0.14

*0.57

11.74±0.18

12.06±0.18

12.19±0.16

12.50±0.13 Ns

3JC10.86±0.37

10.92±0.11

11.25±0.05

11.45±0.12 ns

11.99±0.08

12.41±0.24

12.54±0.19

12.75±0.17 ns

12.19±0.15

12.43±0.19

12.58±0.20

12.83±0.10 Ns

5JC11.52±0.17

11.64±0.10

11.73±0.09

11.99±0.11 ns

12.63±0.09

12.76±0.05

12.94±0.18

13.12±0.20 ns

12.80±0.07

12.71±0.24

12.99±0.19

13.20±0.10 Ns

LSD(0.05)

*1.21

***0.31

**0.48

*0.94

**0.63

*0.65 ns ns

**0.61 ns ns

*0.7

124

Figure 5.4.3 Effect of fertilizer application on kernels per row under different spacingin 2 years, 3 years and 5 years jhum cycles. Vertical line indicates standard error.

Figure 5.4.4 Effect of fertilizer application on kernels per cob under different spacingin 2 years, 3 years and 5 years jhum cycles. Vertical line indicates standard error.

125

Table 5.4.3: The effect of fertilizer application on number of kernels per row under S1, S2and S3 spacing in 2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001

Table 5.4.4: The effect of fertilizer application on number of kernels per cob under S1, S2and S3 spacing in 2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC26.24±0.48

27.38±0.35

27.56±0.17

27.75±0.18

*1.13

31.75±0.33

31.63±0.17

32.79±0.32

33.20±0.61 NS

31.42±0.10

31.79±0.21

32.90±0.33

33.44±0.34

**1.11

3JC28.96±0.34

29.14±0.08

29.43±0.26

30.90±0.10

***1.46

34.59±0.11

35.01±0.33

35.57±0.22

36.11±0.14

**0.97

34.51±0.11

35.05±0.13

35.53±0.22

35.60±0.17

**0.53

5JC32.40±0.12

31.63±0.19

32.31±0.16

32.90±0.29

*0.68

36.67±0.19

37.20±0.20

38.17±0.04

38.58±0.22

***0.96

36.70±0.38

37.39±0.11

38.10±0.08

38.53±0.30

**1.14

LSD(0.05)

***2.71

***1.76

***1.87

***2

***2.07

***2.19

***2.6

***2.47

***2.18

***2.34

***2.57

***2.15


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC270.44±7.03

282.69±5.67

301.63±2.25

306.59±6.78

**18.94

368.47±3.82

382.71±1.52

399.30±2.47

410.65±3.14

***11.35

368.99±5.35

383.21±3.28

401.05±6.54

417.93±2.61

***16.88

3JC317.57±14.90

318.11±3.03

331.03±3.30

353.72±4.86

*35.61

414.76±3.48

434.43±4.46

445.97±7.62

460.25±4.50

**19.62

420.62±6.33

435.73±8.29

446.95±4.26

456.77±5.34

*21.04

5JC373.21±4.22

368.13±4.99

378.91±1.97

394.36±4.96

*15.45

462.95±1.90

474.68±3.50

494.04±6.71

506.11±5.16

***19.36

469.83±2.47

475.05±8.06

494.90±7.86

508.71±0.72

**19.85

LSD(0.05)

***47.12

***33.42

***29.4

***40.63

***46.28

***40.24

***46.67

***45.86

***49.21

***39.31

***45.9

***38.84

126

Figure 5.4.5 Effect of fertilizer application on test weight under different spacing in 2years, 3 years and 5 years jhum cycles. Vertical line indicates standard error.

Figure 5.4.6 Effect of fertilizer application on grain yield under different spacing in 2years, 3 years and 5 years jhum cycles. Vertical line indicates standard error.

127

Table 5.4.5: Test weight (wt. of 1000 grains) under different spacing and fertilizer applicationlevels in 2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001

Table 5.4.6: Grain yield under different spacing and fertilizer application levels in 2, 3 and 5years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC255.33±2.60

264.33±2.40

267.46±1.86

275.67±2.40

**8.20

275.33±3.18

294.33±0.33

297.67±1.45

303.00±1.16

***8.66

277.00±2.08

295.59±1.75

300.00±2.08

303.28±1.36

***7.68

3JC263.67±1.86

273.33±1.20

277.00±3.22

281.67±1.45

**8.33

283.67±1.86

298.14±2.59

304.33±0.67

305.33±0.88

***6.19

284.67±1.45

297.33±2.33

303.67±0.88

306.00±0.58

***6.33

5JC274.20±1.73

279.38±2.91

279.33±3.18

288.73±0.37

*9.34

293.50±3.67

304.05±3.47

309.00±0.58

309.24±1.92

*10.55

293.33±2.19

302.67±3.84

309.67±0.88

311.08±1.45

**8.41

LSD(0.05)

**8.33

*9 ns

**6

*18.16 Ns

***4.66 ns

**7.66 ns

**6

**5.08


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC6274.4±105.1

6790.9±93.11

7333.9±79.22

7683.5±188.8

***542.99

6764.2±127.26

7509.6±37.53

7924.2±87.53

8294.7±46.24

***370.16

6812.9±77.69

7551.3±75.17

8022.5±183.99

8449.9±64.56

***427.40

3JC7614.7±388.7

7903.8±44.11

8337.7±178.16

9057.8±145.1

*1153.95

7842.8±38.07

8636.0±155.82

9047.8±149.53

9367.9±64.86

***731.95

7983.1±149.79

8636.3±159.29

9048.3±99.70

9317.7±93.19

***681.37

5JC8806.7±76.77

9347.2±29.44

9325.0±148.95

9919.9±103.87

***518.23

9051.7±30.18

9622.0±149.49

10177.5±155.52

10435.0±171.47

***555.46

9219.4±85.72

9586.9±238.58

10216.8±164.96

10549.9±40.29

**629.92

LSD(0.05)

***1192.0

***1112.9

***987.2

***862.1

***1078.5

***986.0

***1123.6

***1067.0

***1170.1

***950.57

***11025.7

***867.7

128

Figure 5.4.7 Effect of fertilizer application on harvest index under different spacing in2 years, 3 years and 5 years jhum cycles. Vertical line indicates standard error.

Table 5.4.7: Harvest Index under different spacing and fertilizer application levels in 2, 3 and5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC0.262

±0.0110.256

±0.0060.259

±0.0040.265

±0.008 ns0.320

±0.0190.341

±0.0080.332

±0.0020.335

±0.007 ns0.323

±0.0070.326

±0.0020.335

±0.0100.339

±0.006 ns

3JC0.313

±0.0110.289

±0.0040.290

±0.0070.309

±0.011 ns0.381

±0.0070.385

±0.0090.371

±0.0080.374

±0.008 ns0.375

±0.0060.370

±0.0070.370

±0.0050.371

±0.006 ns

5JC0.350

±0.0090.325

±0.0060.328

±0.0100.348

±0.006 ns0.405

±0.0040.391

±0.0050.400

±0.0060.405

±0.007 ns0.408

±0.0080.385

±0.0110.406

±0.0050.405

±0.006 nsLSD(0.05)

**0.037

***0.033

**0.031

**0.038

**0.061

**0.044

***0.029

**0.031

***0.033

**0.04

**0.034

***0.031

129

5.5 Effect of plant spacing on growth parameters


The height at 15 DAS showed no significant (P<0.05) effect except in

F0 plot in 5JC. Although there was no statistical significance, plants grown under S1

spacing showed comparatively plant height (Figure 5.5.1 & Table 5.5.1).


Plant height at 30DAS showed more significance difference among the

S1, S2 and S3 spacings of each fertilizer treatments. In 2JC, significant difference was

observed among different spacings with F2 level of fertilizer application. In 3JC,

significant difference was observed among different spacings of F0 and F2 fertilizer

levels. In 5JC, significance effect of plant spacing was observed under each of the

fertilizer levels. In all the Fertilizer levels, F2 and F3 showed comparable values

where as plants in S1 showed significantly lower plant height (Figure 5.5.2 & Table

5.5.2).


Plant height at 45DAS also showed low significant response to plant

spacing. Significant difference (P<0.05) in height occurred among the spacings of all

the fertilizer levels. In all the jhum cycles, lowest height occurred in highest plant

density where as similar values were observed between S2 and S3 spacings (Table

5.5.3 & Figure 5.5.3).


At 60DAS, significant difference (P<0.05) among the three spacing

was observed in all the fertilizer levels of 2JC, 3JC and 5JC. The significant different

was due to the wide range between S1 to S2 and S3, and no significant difference was

observed between S2 and S3. From all the combinations of spacings and fertilizer

130

levels, the lowest height of 162.23±4.12cm occurred in S1F0 plot of 2JC and the

maximum height of 232.63±1.36cm was recorded in S3F3 plot of 5JC which

accounted for an increased of about 43% from the lowest height (Figure 5.5.4 & Table

5.5.4).

5.5.5 Effect of plant spacing number of leaves at 15 DAS

Similar to plant height, the number of leaves per plant showed no

significant variations among the different spacings in all the fertilizer levels. Number

of leaves per plant showed narrow range of 5.11 to 5.87 in all the different

combinations of fertilizer levels and spacing (Figure 5.5.5 & Table 5.5.5).


At 30DAS, no statistically significant (P<0.05) difference was

observed among the different spacing in all the fertilizer levels of 2JC, 3JC and 5JC.

The number of leaves per plant showed narrow ranged from 7.08±0.11 (S1F0) of 2JC

to 8.0±0.08 (S3F3) of 5JC (Figure 5.5.6 & Table 5.5.6).


Unlike 15DAS and 30DAS, marked significant variations in number of

leaves per plant were observed at 45DAS among different spacings in all the fertilizer

levels. Again much lower number of leaves was observed in S1 spacing when

compared with that of S2 and S3 spacings. S2 and S3 showed comparable high

number of leaves per plant with no statistically significant difference (Figure 5.5.7 &

Table 5.5.7).


Number of leaves per plant at 60DAS also showed significant

variations among the different spacings in each of the fertilizer levels. Comparative

higher influence of spacing was observed in 2JC. From all the combinations of

131

spacing and fertilizer levels, lowest number of leaves per plant occurred in

10.82±0.03 (S1F0) in 2JC and highest number in 13.68±0.07 (S3F2) of 5JC which

accounted for an increase of about 26% (Figure 5.5.8 & Table 5.5.8).

5.5.9 Biomass production

The plant biomass at the time of maturity harvest in terms of dry weight showed

significant variations among the S1, S2 and S3 spacings in all the fertilizer levels of

2JC, 3JC and 5JC. Similar to plant height and number of leaves per plant, plants in S1

spacing showed comparatively lower biomass production and similar values were

observed in S2 and S3. The lowest plant biomass of 264.50±7.37 gm (S1F0) of 2JC to

the highest of 390.93±4.29gm (S3F3) of 5JC accounted for 47.79% increase from the

lowest value (Figure 5.5.9 & Table 5.5.9).

132

Figure 5.5.1 Effect of spacing on plant height at 15 DAS under different fertilizerapplication levels in 2 years, 3 years and 5 years jhum cycles. Vertical line indicatesstandard error.

c


133

Table 5.5.1: Effect of spacing on plant height at 15DAS under different levels offertilizer applications in 2, 3 and 5 years jhum cycles. Mean ±SEM.

* = P<0.05, ** = P<0.01, *** = P<0.001


* = P<0.05, ** = P<0.01, *** = P<0.001

S1F0 S2F0 S3F0LSD(0.05) S1F1 S2F1 S3F1

LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC13.85±0.46

14.43±0.48

14.48±0.67 ns

15.80±0.11

16.78±0.48

16.70±0.60 ns

17.16±0.36

17.30±0.34

17.97±0.29 ns

18.14±0.56

18.10±0.23

18.39±0.28

ns

3JC14.44±0.53

14.37±0.62

15.14±0.48 ns

16.91±0.16

17.20±0.31

16.91±0.34 ns

17.98±0.34

18.19±0.30

18.27±0.47 ns

18.54±0.33

18.89±0.23

18.86±0.44

ns

5JC14.90±0.12

14.78±0.35

16.87±0.18

**1.96

16.72±0.54

17.07±0.41

17.11±0.34 ns

17.44±0.42

18.52±0.52

18.13±0.14 ns

18.63±0.29

19.11±0.20

18.97±0.13

ns


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JCSEM

43.16±1.95

48.18±1.90

50.87±2.94 ns

52.88±1.96

59.57±2.32

61.59±2.94 ns

56.60±1.34

63.62±1.66

61.30±SEM

*7.01

60.66±2.71

66.94±1.81

65.69±1.73

ns

3JCSEM

52.72±1.57

61.76±2.21

63.46±1.96

*9.03

56.83±1.36

62.53±1.60

64.90±2.43 ns

61.27±0.51

69.63±1.24

68.67±SEM

**7.40

63.70±1.96

71.41±3.18

70.44±3.39

ns

5JCSEM

68.28±1.40

83.79±1.54

81.30±3.01

**13.01

71.14±2.70

82.32±2.09

84.83±3.27

*11.17

74.67±1.35

87.18±1.83

87.69±SEM

**12.51

79.87±1.15

89.38±1.57

89.56±1.57

**9.51

134



135


* = P<0.05, ** = P<0.01, *** = P<0.001


* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC79.74±0.84

85.64±1.56

83.55±1.09

*5.90

89.46±0.85

100.03±3.37

98.28±2.38

*8.81

97.52±4.27

112.10±4.15

115.34±3.51

*2.58

101.92±2.01

118.50±4.15

122.42±6.62

*16.58

3JC89.60±3.32

97.83±2.92

106.73±2.98

*17.13

101.63±1.61

103.21±2.47

111.11±3.35 ns

109.35±1.43

118.93±2.37

122.84±2.54

*9.57

121.42±0.78

131.67±4.49

131.26±1.24 ns

5JC142.34±3.56

159.81±3.50

153.94±2.40

*11.60

157.08±2.65

166.56±2.89

168.37±1.20

*9.47

163.85±1.81

171.34±4.21

175.67±1.45 ns

170.67±2.03

184.26±3.14

181.31±1.22

*10.64


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC162.23±4.12

185.61±3.38

188.32±1.48

**23.37

169.03±3.84

195.74±3.36

197.45±4.72

**26.71

177.50±5.02

207.87±2.62

206.25±1.92

**28.75

184.63±5.14

215.34±2.49

212.72±3.29

**28.08

3JC165.38±2.10

190.51±5.36

193.98±2.55

**25.13

177.44±5.60

200.58±1.64

202.05±2.01

**23.13

186.50±4.55

210.98±2.39

209.45±4.19

**22.94

196.14±5.32

218.72±1.00

217.52±2.60

**21.37

5JC183.33±3.84

205.52±2.04

206.89±1.42

**22.18

194.88±3.47

212.32±2.92

211.03±1.84

**16.15

201.41±4.70

217.45±2.10

217.83±2.27 *

212.54±1.36

229.92±0.28

232.63±1.36

***17.37

136

Figure 5.5.5 Effect of spacing on number of leaves per plant at 15 DAS underdifferent fertilizer application levels in 2 years, 3 years and 5 years jhum cycles.Vertical line indicates standard error.


137

Table 5.5.5: Effect of spacing on number of leaves per plant at 15DAS under differentlevels of fertilizer applications in 2, 3 and 5 years jhum cycles. Mean ±SEM.

* = P<0.05, ** = P<0.01, *** = P<0.001


* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JCSEM

5.11±0.04

5.29±0.08

5.44±0.10 ns

5.55±0.11

5.58±0.11

5.65±0.10 ns

5.57±0.11

5.63±0.13

5.67±0.11 ns

5.81±0.07

5.77±0.11

5.71±0.10 ns

3JCSEM

5.15±0.09

5.23±0.17

5.45±0.11 ns

5.55±0.09

5.59±0.11

5.62±0.06 ns

5.61±0.09

5.68±0.04

5.69±0.08 ns

5.83±0.03

5.84±0.03

5.87±0.05 ns

5JCSEM

5.48±0.06

5.53±0.12

5.58±0.10 ns

5.59±0.09

5.61±0.06

5.64±0.08 ns

5.65±0.11

5.69±0.07

5.71±0.08 ns

5.83±0.03

5.84±0.03

5.86±0.03 ns


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC7.08

±0.117.60

±0.047.65

±0.087.68

±0.08**0.52

7.13±0.04

7.65±0.06

7.64±0.07

7.71±0.10

**0.51

7.14±0.20

7.67±0.07

7.67±0.08

7.69±0.08

*0.53

3JC7.57

±0.027.69

±0.047.86

±0.097.92

±0.10*0.29

7.64±0.02

7.74±0.03

7.88±0.09

7.94±0.10 ns

7.63±0.02

7.77±0.03

7.90±0.09

7.94±0.10 ns

5JC7.71

±0.097.82

±0.047.91

±0.078.02

±0.08 ns7.76

±0.067.87

±0.027.96

±0.078.03

±0.06*0.20

7.77±0.05

7.89±0.00

7.99±0.07

8.05±0.08

*0.21

LSD(0.05)

**0.48

*0.21 ns ns

***0.5

*0.21 ns ns

*0.49

*0.22 ns ns

138



139


* = P<0.05, ** = P<0.01, *** = P<0.001


*= P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC 9.85±0.31

10.98±0.25

11.13±0.15

*1.12

10.13±0.36

11.48±0.15

11.50±0.05

**1.34

10.39±0.07

11.53±0.14

11.63±0.14

***1.14

10.87±0.20

11.59±0.17

11.61±0.03

*0.71

3JC 10.15±0.13

11.40±0.03

11.45±0.06

***1.25

10.37±0.10

11.57±0.05

11.68±0.01

***1.20

10.68±0.07

11.74±0.02

11.78±0.03

***1.05

11.00±0.15

11.80±0.09

11.81±0.09

**0.79

5JC 10.37±0.09

11.84±0.01

11.83±0.05

***17.43

11.20±0.15

11.92±0.02

12.01±0.06

**0.71

11.30±0.06

12.10±0.10

12.11±0.08

***0.80

11.67±0.07

12.25±0.03

12.21±0.04

***0.54


LSD(0.05) S3F0 S3F1 S3F2 S3F3

LSD(0.05)

2JC10.59±0.17

10.71±0.28

11.25±0.07

11.50±0.09

*0.65

11.98±0.05

12.35±0.05

12.34±0.06

12.56±0.02

***0.21

12.09±0.06

12.34±0.02

12.41±0.04

12.55±0.06

**0.21

3JC10.49±0.36

10.69±0.32

10.97±0.24

11.17±0.05 ns

12.06±0.15

12.44±0.30

12.54±0.37

12.78±0.34 ns

12.18±0.11

12.45±0.33

12.58±0.27

12.99±0.25 ns

5JC10.87±0.34

11.32±0.07

11.98±0.17

12.34±0.14

**1.02

12.48±0.28

12.75±0.31

13.24±0.15

13.68±0.07

*0.76

12.27±0.54

12.80±0.30

13.25±0.18

13.66±0.05 ns

LSD(0.05) ns ns

*0.73

***0.84 ns ns ns

*0.9 ns ns

*0.67

**0.67

140

Figure 5.5.9 Effect of spacing on biomass production at maturity harvest underdifferent fertilizer application levels in 2 years, 3 years and 5 years jhum cycles.Vertical line indicates standard error

Table 5.5.9: Effect of spacing on biomass production at maturity harvest underdifferent levels of fertilizer application in 2, 3 and 5 years jhum cycles. Mean ±SEM

*= P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC 264.50±7.37

318.50±14.40

316.50±3.97

*52

292.50±7.70

331.00±6.61

347.00±3.50

**38.5

311.50±4.44

358.50±4.58

359.65±3.16

***47

319.50±3.12

371.50±6.08

374.20±4.09

***52

3JC 267.77±4.91

308.55±3.87

319.66±3.01

***40.78

301.12±2.11

336.59±2.24

350.15±3.33

***13.55

316.10±3.02

366.17±2.34

367.19±1.37

***50.07

322.38±6.39

376.03±5.67

377.08±2.28

***53.64

5JC 292.60±4.50

335.80±2.75

337.72±2.78

***43.19

316.87±5.96

369.59±2.84

373.41±3.95

***52.72

323.40±5.30

381.54±2.01

377.46±2.96

***54.05

327.13±5.96

386.11±1.79

390.93±4.29

***58.98

141

5.6 Effect of plant spacing on yield parameters

5.6.1 Length of cob

Length of cob showed highly significant (P<0.001) difference among

the three spacing in each of the fertilizer levels in 2JC. Significant (P<0.05) difference

was also found among the three spacings in all the fertilizer levels of 3JC and 5JC.

Length of cob of S2 and S3 showed comparable values where as considerably shorter

length was observed in S1 spacing. The difference from the shortest length of

14.70±0.17 (S1F0)cm in 2JC to the longest of 22.08±0.39 cm(S3F3) in 5JC accounted

for about 50% increase from the shortest length (Figure 5.6.1 & Table 5.6.1).

5.6.2 Kernel rows per cob

Kernel rows per cob also showed significant (P<0.05) variations

among difference spacings with much lesser number of rows in S1 spacing when

compared with S2 and S3. The increase in kernel rows per cob from the minimum and

maximum values in each fertilizer levels accounted for 13.98% in F0, 16.79% in F1,

11.36% in F2 and 13.14% in F3 of 2JC. In 3JC, the increase from the from the

minimum and maximum values in each fertilizer levels accounted for 12.20% in F0,

13.86% in F1, 11.86% in F2 and 12.08% in F3. Lower range between the minimum

and maximum values was observed in 5JC which accounted for 11.13% increase in

F0, 9.17% in F1, 10.75% in F2 and 10.14% in F3 respectively (Figure 5.6.2 & Table

5.6.2).

The ranged between the lowest number of kernel rows per cob in

10.30±0.08 (S1F0) in 2JC to the highest of 13.20 (S3F3) in 5JC accounted for 28.15%

increase from the lowest value.

142

5.6.3 Kernel per row

The number of kernels per row showed highly significant (P<0.001)

variations among the three spacings in all the fertilizer levels of 2JC, 3JC and 5JC. S2

and S3 showed no significant difference where as S1 showed significant difference

with S2 and S3 due to its comparatively lower values in all the fertilizer levels. From

all the combinations of spacings, fertilizer levels and different jhum cycles, the

difference between the lowest value of 26.24±0.48 (S1F0) in 2JC to the highest value

of 38.58±0.30 (S3F2) in 5JC accounted for 47% increase from the lowest value

(Figure 5.6.3 & Table 5.6.3).

5.6.4 Kernels per cob

The number of kernels per cob also showed highly significant

(P<0.001) variations between S1 with S2 and S3 in all the fertilizer application levels.

The difference between the minimum and the maximum number of kernels per cob

accounted for 19.72 in F0, 16.10% in F1, 19.37% in F2 and 20.50% in F3 of 2JC;

18.10% in F0, 20.27% in F1, 20.72% in F2 and 15.21% F3 in 3JC and, 13.27% in F0,

18.20% in F1, 17.91% in F2 and 17.12% in F3 of 5JC (Figure 5.6.4 & Table 5.6.4).

Among the different combinations of spacings and fertilizer levels in

2JC, 3JC and 5JC, the difference between the lowest number of kernels per cob of

270.44±7.03 (S1F0) in 2JC to the highest number of 508.71 (S3F3) in 5JC accounted

for 88% increase from the lowest value.

5.6.5 Test weight

The test weight showed significant (P<0.05) difference among the S1,

S2 and S3 spacings which was due to the marked lower values in S1 spacing in all the

143

fertilizer levels. The combination of wider spacing with higher level of fertilizer

application resulted in the increase in test weight. The lowest TW of 255.33±2.60 gm

(S1F0) in 2JC to 311.08±1.45 gm (S3F3) in 5JC accounted for 21.83% from the

minimum value (Figure 5.6.5 & Table 5.6.5).

5.6.6 Grain yield

Grain yield was significantly (P<0.05) affected by plant spacing in all

fertilizer levels except in F0 and F3 in 3JC and, F1 in 5JC. Lower grain yield per

hectare was observed in highest density spacing. The range from the minimum grain

yield to the maximum yield among the three spacing accounted for 8.58%, 11.19%,

9.38% and 9.97% increase in F0, F1, F2 and F3 of 2JC; 4.83%, 9.26%, 8.52% and

2.86% in F0, F1, F2 and F3 of 3J and, 4.68%, 2.56%, 9.56% and 6.35% increase in

F0, F1, F2 and F3 of 5JC (Figure 5.6.6 & Table 5.6.6).

5.6.7 Harvest Index

Harvest index was significantly (P<0.05) influenced by plant spacing

in which the highest density spacing of S1 resulted in reduction of HI. The maximum

HI in 2JC, 3JC and 5JC were 0.339±0.006 (S3F3), 0.385±0.009 (S2F1) and

0.408±0.008 (S3F0) respectively. Comparatively higher HI was observed in all the

plots of 5JC (Figure 5.6.7 & Table 5.6.7).

144

Figure 5.6.1 Effect of spacing on length of cob under different fertilizer applicationlevels in 2 years, 3 years and 5 years jhum cycles. Vertical line indicates standarderror

Figure 5.6.2 Effect of spacing on kernel rows per cob under different fertilizerapplication levels in 2 years, 3 years and 5 years jhum cycles. Vertical line indicatesstandard error

145

Table 5.6.1: Effect of spacing on length of cob under different levels of fertilizer applicationin 2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001

Table 5.6.2: Effect of spacing on kernel rows per cob under different levels of fertilizerapplication in 2, 3 and 5 years jhum cycles. Mean ±SEM.

* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC 14.70±0.17

17.48±0.30

17.50±0.36

***2.77

14.87±0.12

18.54±0.21

18.64±0.33

***3.67

17.31±0.14

18.80±0.16

18.98±0.17

***1.49

15.90±0.31

19.07±0.36

19.10±0.31

***3.16

3JC 16.00±0.40

18.94±0.18

18.90±0.12

***2.9

17.07±0.19

19.69±0.25

19.79±0.23

***2.62

18.64±0.25

20.35±0.35

20.43±0.36

*1.71

18.87±0.18

20.62±0.23

20.58±0.24

**1.71

5JC 17.73±0.38

20.66±0.12

20.65±0.16

***2.91

18.62±0.30

21.32±0.37

21.42±0.38

**2.69

19.40±0.09

21.64±0.38

21.75±0.38

**2.23

20.16±0.18

22.08±0.31

22.08±0.39

**1.91


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC 10.30±0.08

11.61±0.22

11.74±0.18

**1.30

10.32±0.12

12.10±0.07

12.06±0.18

***1.73

10.95±0.15

12.18±0.15

12.19±0.16

**1.23

11.05±0.23

12.37±0.14

12.50±0.13

**1.32

3JC 10.86±0.37

11.99±0.08

12.19±0.15

*1.12

10.92±0.11

12.41±0.24

12.43±0.19

**1.49

11.25±0.05

12.54±0.19

12.58±0.20

**1.29

11.45±0.12

12.75±0.17

12.83±0.10

***1.30

5JC 11.52±0.17

12.63±0.09

12.80±0.07

***1.10

11.64±0.10

12.76±0.05

12.71±0.24

**1.06

11.73±0.09

12.94±0.18

12.99±0.19

**1.21

11.99±0.11

13.12±0.20

13.20±0.10

**1.13

146

Figure 5.6.3 Effect of spacing on kernels per row under different fertilizer applicationlevels in 2 years, 3 years and 5 years jhum cycles. Vertical line indicates standarderror.

Figure 5.6.4 Effect of spacing on kernels per cob under different fertilizer applicationlevels in 2 years, 3 years and 5 years jhum cycles. Vertical line indicates standarderror.

147

Table5.6.3: Effect of spacing on kernel per row under different levels of fertilizer applicationin 2, 3 and 5 years Jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001

Table5.6.4: Effect of spacing on kernel per cob under different levels of fertilizer applicationin 2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC 10.30±0.08

11.61±0.22

11.74±0.18

**1.30

10.32±0.12

12.10±0.07

12.06±0.18

***1.73

10.95±0.15

12.18±0.15

12.19±0.16

**1.23

11.05±0.23

12.37±0.14

12.50±0.13

**1.32

3JC 10.86±0.37

11.99±0.08

12.19±0.15

*1.12

10.92±0.11

12.41±0.24

12.43±0.19

**1.49

11.25±0.05

12.54±0.19

12.58±0.20

**1.29

11.45±0.12

12.75±0.17

12.83±0.10

***1.30

5JC 11.52±0.17

12.63±0.09

12.80±0.07

***1.10

11.64±0.10

12.76±0.05

12.71±0.24

**1.06

11.73±0.09

12.94±0.18

12.99±0.19

**1.21

11.99±0.11

13.12±0.20

13.20±0.10

**1.13

147


* = P<0.05, ** = P<0.01, *** = P<0.001


* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC 10.30±0.08

11.61±0.22

11.74±0.18

**1.30

10.32±0.12

12.10±0.07

12.06±0.18

***1.73

10.95±0.15

12.18±0.15

12.19±0.16

**1.23

11.05±0.23

12.37±0.14

12.50±0.13

**1.32

3JC 10.86±0.37

11.99±0.08

12.19±0.15

*1.12

10.92±0.11

12.41±0.24

12.43±0.19

**1.49

11.25±0.05

12.54±0.19

12.58±0.20

**1.29

11.45±0.12

12.75±0.17

12.83±0.10

***1.30

5JC 11.52±0.17

12.63±0.09

12.80±0.07

***1.10

11.64±0.10

12.76±0.05

12.71±0.24

**1.06

11.73±0.09

12.94±0.18

12.99±0.19

**1.21

11.99±0.11

13.12±0.20

13.20±0.10

**1.13

147


* = P<0.05, ** = P<0.01, *** = P<0.001


* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC 10.30±0.08

11.61±0.22

11.74±0.18

**1.30

10.32±0.12

12.10±0.07

12.06±0.18

***1.73

10.95±0.15

12.18±0.15

12.19±0.16

**1.23

11.05±0.23

12.37±0.14

12.50±0.13

**1.32

3JC 10.86±0.37

11.99±0.08

12.19±0.15

*1.12

10.92±0.11

12.41±0.24

12.43±0.19

**1.49

11.25±0.05

12.54±0.19

12.58±0.20

**1.29

11.45±0.12

12.75±0.17

12.83±0.10

***1.30

5JC 11.52±0.17

12.63±0.09

12.80±0.07

***1.10

11.64±0.10

12.76±0.05

12.71±0.24

**1.06

11.73±0.09

12.94±0.18

12.99±0.19

**1.21

11.99±0.11

13.12±0.20

13.20±0.10

**1.13

148

Figure 5.6.5 Effect of spacing on test weight under different fertilizer applicationlevels in 2 years, 3 years and 5 years jhum cycles. Vertical line indicates standarderror.

Figure 5.6.6 Effect of spacing on grain yield under different fertilizer applicationlevels in 2 years, 3 years and 5 years jhum cycles. Vertical line indicates standarderror.

149

Table5.6.5: Effect of spacing on Test weight (1000 grain wt.) under different levels offertilizer application levels in 2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001

Table 5.6.6: Effect of spacing on grain yield under different levels of fertilizerapplication in 2, 3 and 5 years jhum cycles. Mean ±SEM.

* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC 255.33±2.60

275.33±3.18

277.00±2.08

**20

264.33±2.40

294.33±0.33

295.59±1.75

***30

267.46±1.86

297.67±1.45

300.00±2.08

***30.20

275.67±2.40

303.00±1.16

303.28±1.36

***27.33

3JC 263.67±1.86

283.67±1.86

284.67±1.45

***20

273.33±1.20

298.14±2.59

297.33±2.33

***24

277.00±3.22

304.33±0.67

303.67±0.88

***26.66

281.67±1.45

305.33±0.88

306.00±0.58

***23.66

5JC 274.20±1.73

293.50±3.67

293.33±2.19

**19.13

279.38±2.91

304.05±3.47

302.67±3.84

**23.28

279.33±3.18

309.00±0.58

309.67±0.88

***29.66

288.73±0.37

309.24±1.92

311.08±1.45

***20.51


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC 6274.4±105.1

6764.2±127.3

6813.0±77.7

*489.82

6790.9±93.1

7509.7±37.5

7551.4±75.2

***718.71

7333.9±79.2

7924.2±87.5

8022.5±184.0

*590.29

7683.5±188.9

8294.8±46.2

8449.9±64.6

**611.28

3JC 7614.7±388.8

7842.8±38.1

7983.1±149.8 ns

7903.9±44.1

8636.0±155.8

8636.3±159.3

*732.13

8337.8±178.2

9047.9±149.5

9048.3±99.7

*710.10

9057.8±145.2

9368.0±64.9

9317.7±93.2 ns

5JC 8806.8±76.8

9051.7±30.2

9219.5±85.7

*244.91

9347.2±29.4

9622.1±149.5

9586.9±238.6 ns

9325.0±148.9

10177.6±155.5

10216.8±165.0

*852.53

9919.9±103.9

10435.0±171.5

10549.9±40.3

*515.07

150

Figure 5.6.7 Effect of spacing on harvest index under different fertilizer applicationlevels in 2 years, 3 years and 5 years jhum cycles. Vertical line indicates standarderror.

Table 5.6.7: Effect of spacing on Harvest Index (HI) under different levels fertilizerapplication in 2, 3 and 5 years jhum cycles. Mean ±SEM

* = P<0.05, ** = P<0.01, *** = P<0.001


LSD(0.05) S1F2 S2F2 S3F2

LSD(0.05) S1F3 S2F3 S3F3

LSD(0.05)

2JC 0.262±0.011

0.320±0.019

0.323±0.007

*0.05

0.256±0.006

0.341±0.008

0.326±0.002

***0.07

0.259±0.004

0.332±0.002

0.335±0.010

***0.07

0.265±0.008

0.335±0.007

0.339±0.006

***0.07

3JC 0.313±0.011

0.381±0.007

0.375±0.006

**0.06

0.289±0.004

0.385±0.009

0.370±0.007

***0.08

0.290±0.007

0.371±0.008

0.370±0.005

***0.07

0.309±0.011

0.374±0.008

0.371±0.006

**0.06

5JC 0.350±0.009

0.405±0.004

0.408±0.008

**0.05

0.325±0.006

0.391±0.005

0.385±0.011

**0.06

0.328±0.010

0.400±0.006

0.406±0.005

***0.07

0.348±0.006

0.405±0.007

0.405±0.006

**0.06

151

Chapter – VI

Discussion

6.1 Effect of NPK fertilizer on growth performance

6.1.1 Effect of fertilizer applications on plant height

The sowing of seeds on 24 March coincided with the summer rain

resulted in the early germination of seeds. The significant difference in height among

the fertilizer different levels of fertilizer application with better plant height under

higher rate of fertilizer application may be due to the improvement of seedling vigor

by the availability of soil nutrients for the developing seedlings. Improvement of

seedling vigor is necessary for the survival and yield of crops plants. The minimum

height in plots without fertilizer application and the increasing in plant height with

increasing in fertilizer application indicated the early response of maize seedlings to

soil nutrient availability. The non significant difference in plant height among the

jhum cycles in most of the fertilizer levels indicated the low response to different

jhum cycles a the initial stage of growth.

The plant height under different fertilizer levels at 30DAS exhibited a

marked shift from that of the plant height at 15DAS as highly significant difference

occurred among the jhum cycles. Less significant variations among the fertilizer plots

in each of the spacings may be due to depletion of soil nutrients due to leaching by

rainfall and that the highly significant difference among the jhum cycles may be

attributed to the different natural soil condition among the jhum cycles.

The increase in the significant level from that of 30DAS in plant height

of maize under different fertilizer levels may be due to response of plants to the

second dose of NPK fertilizer which was applied at 30DAS. The higher percentage

152

increase from the minimum height to the maximum height in 2JC and 3JC may be due

to the high influence of nutrient application in these two jhum sites of poorer soil

nutrient properties than the 5JC. High growth rate in height during the period of 30 to

45DAS coincided with the increasing in rainfall which enhances growth performance.

Compared to 2JC and 3JC, higher growth rate was observed among the plants in the

fertilizer plots of 5JC.

Measurement of plant height at 60DAS showed highest growth rate in

plants under different fertilizer levels in 2JC and 3JC where as reduction is growth

rate was observed in 5JC when compared with that of the growth rate at 45DAS.

Despite of the wide range in plant height between plants of 2JC and 3JC to that of the

corresponding treatment in 5JC in 45DAS, the range become narrower due to the high

growth rate of plants in 2JC and 3JC.

From the observation plant growth performance in terms of height, it is

obvious that soil nutrient deficit is one of the major limiting factors for plant growth

in the different jhum cycles of Mizoram. Fertilizer application and longer jhum cycle

induced vigorous growth during the 15 to 45DAS. Plant height is one of the crucial

factors which determines the survival and productivity of the plant. Higher plant

height has better light interception which facilitates higher photosynthetic rates under

favourable condition. From the observation of highest plant height corresponding with

highest fertilizer application, it might be suggested that increase the levels of NPK

fertilizer application might still enhance the growth performance of the mimpui

variety of maize.

6.1.2 Effect of NPK fertilizer application on number of leaves per plant

The non-significant and low significant variations in number of leaves

per plant in all the fertilizer levels as well as among the jhum cycles indicted that the

153

leaves production was uniform regardless of soil nutrient input and difference in jhum

cycles. Although the highly significant variation in plant height at this growth stage

did not induced much variations in leaves production as all the plants under different

fertilizer application levels as well as jhum cycles showed narrow range in number of

leaves per plant.

As the growth progressed, higher variations among the plants under

different fertilizer applications as well as the jhum cycles indicated that the influence

of soil nutrient availability became more evident. More variations were observed at

45DAS in the number of leaves per plant. Similar trend with that of plant height of

increasing number of leaves with increasing fertilizer application levels as well as the

jhum cycles was still observed at 45DAS.

Despite of the higher significant difference in height at 60DAS, the

number of leaves at 60DAS showed lesser significant levels between fertilizer plots as

well as the jhum cycles. This indicated that the number leaf production was less

affected by fertilizer input and jhum cycles, and the higher variations in plant height

did not necessarily induced greater number of leaves per plant. Thus, the increase in

height might be due to the increase in internode length rather than the production of

more nodes for leaf production.

6.1.3 Effect of NPK fertilizer onpPlant dry biomass

The plant biomass production was also strongly affected by fertilizer

applications. Under the same spacing, the occurrence of lowest biomass production in

plots without fertilizer input and the increase with increase in fertilizer application

levels showed similar trend with that of plant height and number of leaves per plant.

Plant biomass production was comparable between the fertilizer plots of S2 and S3

spacings. The sharp increase in biomass production from F0 towards F2 and the lesser

154

increased between the F2 and F3 plots in S1, S2 and S3 spacing indicated that the

affect of fertilizer on biomass production was more pronounced between F0 to F2 and

further increase from F2 to F3 level had lesser impact on biomass production.

6.2 Effect of NPK fertilizer application on yield parameters

6.2.1 Length of cob

The length of cob which is a important yield parameter was

significantly affected by fertilizer application showing wide range of less

than15.00cm to greater than 19.00 cm in 2JC, 16.00cm to greater than 20.00cm in

3JC and, less than 18.00cm to greater than 22.00cm in 5JC among the spacing and

fertilizer treatment. This implied the strong impact of space and nutrient availability

on growth and the resultant biomass production of maize plant.

6.2.2 Kernel rows per cob

The number of kernel rows per cob is one of the important yield

parameters than determine grain yield in maize. Although increasing trend of kernel

rows per cob was observed from the F0 plot toward F3 plot in all the three spacing,

there was only few significant difference. The inter jhum comparison also showed

significant increase from 2JC toward 5JC in all the fertilizer plots of S1 but less

significant variations in fertilizer plots of S2 and S3.

6.2.3 Kernels per row

Unlike kernel rows per cob, significant increase in the number of

kernel from F0 toward F3 except in S2 spacing of 2JC indicated the strong impact of

NPK fertilizer under different plant spacing. High rate of increased in number of

kernels per row was observed from F0 toward F2 indicating the best response to NPK

fertilizer by maize plant in the F1 and F2 application rate.

155

The highly significant increase in number of kernels per row 2JC to 5JC indicated the

soil condition of longer jhum cycles might induced more kernels per row in maize.

From the uniform increase in kernels per row from 2JC to 5JC, it is suggested that

logner jhum cycles may induce further increase in number of kernels per row.

6.2.4 Kernels per cob

The similar pattern between length of cob and kernels per row of

significant increase in with increase fertilizer levels as well as with the increase in

jhum cycle resulted in the increase in total number of kernels per cob from plot

without fertilizer application toward the highest level of fertilizer application as well

as with the longer jhum cycles. Considering the overall range under different fertilizer

application, spacing and jhum cycles, the wide range of the number of kernels per

cob, it is evident that this was one of the most variable parameters and it could be

crucial determinants of grain yield.

6.2.5 Test weight

The test weight was highly influenced by NPK fertilizer application

under different spacing which indicated that NPK fertilizer induced the improvement

of the quality of the kernel which manifested in the greater weight of 1000 seed

grains. The significant increase in test weight from the 2JC to 5JC was also a strong

determinant of grain yield of maize.

6.2.6 Grain yield/ha

The grain yield per hectare which was extrapolated from the yield per

plant indicated the strong effect of fertilizer on grain yield of maize. Considering the

increased in grain yield from the lowest yield in the highest density spacing (55cm x

20cm) without fertilizer application to the highest fertilizer application (120:60:40

kg/ha of NPK) with wider spacing (60cm x 25cm), the productivity of maize depend

156

strongly on the cultural practice and selection of the most appropriate spacing and

fertilizer input is the prerequisite. The strong influence of jhum cycles also indicated

its impact of the yield of maize.

Although harvest index showed no significant variations among the

fertilizer plots under different spacing, the significant difference among the jhum

cycles indicated the grain yield per gram of biomass produced increases with increase

in jhum cycles.

6.3 Effect of plant spacing on growth performance

6.3.1 Plant height

The effect of spacing on plant height increases with the progressed of

the growth period and at 60DAS, spacing induced significant difference in plant

height. This less significant variations at the early stage of growth was attributed to

the sufficient space for plant at this stage. As the growth progressed more spatial

competition in the high density spacing resulted in the reduction in plant height at S1

spacing of 55cm x 20cm that 90,909 plants per hectare. The S2 and S3 spacing of

75cm x 20cm (66,666 plants/ha) and 60cm x 25cm (66,666 plants/ha) showed

comparable growth rates.

6.3.2 Number of leaves per plant

The effect spacing on the number of leaves per plant also increased

with the increasing growth period with significant variations among the S1, S2 and S3

spacings in all the fertilizer application levels. Number of leaves was greatly reduced

in highest plant density of S1 spacing.

6.3.3 Biomass production

Biomass production was strongly influenced by spacing with great

reduction in plant dry biomass in S1 spacing. At high density planting, plants compete

157

of vertical growth for better light inception which led to production of weak slender

stalk in plants. The greater plant height and number of leaves felicitates high

photosynthetic rates as well as larger photosynthetic area which improves further

growth and development.

6.3.4 Effect of spacing on yield parameters

The S1, S2, and S3 had strong similar impact on length of cob, kernel

rows per cob, kernels per row, kernels per cob and seed test weight which were the

determinants of the grain yield. The S1 spacing of high density planting (90,909

plants/ha) considerable reduce the yield parameters.

The impact of spacing on grain yield was less significant when compared with that of

the effect of fertilizer application.

The harvest index (HI) was strongly affected by spacing with low HI in the highest

density plant of 55cm x 20cm. This implied that despite of the lowest biomass

production in S1 spacing in each of fertilizer plots; the grain yield was proportionately

lower which resulted in lower HI.

158

Chapter VI

SUMMARY AND CONCLUSION

1. The study was carried out at the Edenthar locality which is at the outskirt of

Aizawl city.

2. The jhum cycles viz. 2 years, 3 years and 5 years cycles were selected to study

the extent of the influence of different jhum cycles on growth and productivity

of maize.

3. Most promising local variety of maize called ‘Mimpui” was selected as it has

a high potential for commercial production of corn to meet various demands

for human consumption as well as animal feeds.

4. Maize were grown under four levels of Nitrogen, phosphorus and potassium

fertilizer treatments of 80N:40P:20K, 100N:50P:30K, 120N:60P:40K (NPK

kg/ha) and Control (Without NPK) with combination of three different spacing

of 75cm x 20 cm, 60 cm x 25 cm and 55cm x 20 cm.

5. Local maize variety grown under four levels of fertilizer treatments and two

levels of spacing in three 2 years, 3 years and 5 years jhum cycles showed

significant response in growth performance and yield characteristics

6. The variations in plant height and number of leaves per plant became more

pronounced with the progress in growth period.

7. Fertilizer significant enhanced seedling vigor and plant growth.

8. Spacing also significantly affected plant growth which became more evident

with increase in growth period as the competition for space and nutrient

increases.

159

9. Highly density spacing of 55cm x 20 cm greatly reduce the growth and yield

performance.

10. In most of the growth and yield parameters, lowest values were observed in

plot with highest density and without fertilizer application where as plant

spacing of 60cm x 25 cm showed maximum values in most of the parameters.

11. Jhum cycles significantly influenced growth performance in which poor

growth was observed in shorter jhum cycle of 2 years when compared with 5

years jhum cycles.

12. Yield parameters were highly influenced by fertilizer application which

increased with increase in fertilizer input.

13. Length of cob, number of kernels per row and test weight were the parameters

which strongly influenced the grain yield.

14. Minimum grain yield of 6274.4 kg/ha occurred in highest plant spacing with

no fertilizer application in 2 years jhum cycle.

15. Highest grain yield of 10549.9 kg/ha occurred in the 5 years jhum cycle with

highest level of fertilizer application (120: 80 : 40 NPK per hectare)

16. From this experiment, it is evident that low soil nutrient under frequent jhum

cycles is the major limiting factor for growth and yield of maize in the hilly

slopes of Mizoram.

17. Considering the growth and yield under the three spacing, 60cm x 25cm is

likely to be the most promising.

From this study, considering the overall effect of fertilizer, spacing and

jhum cycles; the increased from the minimum values to the maximum values

accounted for 43% in plant height at 60DAS, 26% in number of leaves at 60DAS,

160

47.79% in biomass per plant, 50% in length of cob, 28.15% in kernel rows per cob,

88% in kernels per cob, 21.83% in seed test weight, 68.14% in grain yield/ha, 54.58%

in harvest index. This strongly indicated that optimization of cultural practice in in

terms of spacing, fertilizer input and jhum cycles is needed for sustainable agriculture

system even under jhum cultivation without compromising the yield of the Mimpui

variety.

Maize is a nutrient demanding crop and due to its high uptake rate of

available nitrogen, phosphorus and potassium from soil, fertilizer application in the

successive cropping season may be prerequisite in similar jhum cycles to supplement

the nutrient removal of the previous crop. Also due to the acidic condition of the soil,

careful monitoring in application of acidic fertilizer like urea needed to be conducted

to prevent setting up of unfavourable soil condition such as aluminium toxicity. From

this experiment, it is observed that the Mimpui is a high yielding variety that could be

promoted for commercial corn production. Considering the strong effect of NPK

fertilizer in grain yield and at the same time the delicate soil condition under jhum

cultivation, it is suggested that 5 years jhum cycle with lower rate of fertilizer

application (80:40:20 NPK kg/ha) with spacing of 60cm x 25cm may be adopted.

161

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